Only 25% of healthcare organizations have deployed generative AI solutions, but that is expected to more than double next year as executives see opportunities to automate clinical documentation and improve patient communication.
According to a new KLAS report, 58% of healthcare executives say their organization is likely to implement or purchase a solution within the next year. Larger organizations, particularly hospitals with more than 500 beds, are more inclined to invest in a solution than smaller organizations, according to a new KLAS Research report.
Larger providers and payers have more resources to adopt generative AI solutions more swiftly. "In addition, larger organizations often have data more readily available and employ data scientists and specialists who can effectively develop, implement, and drive outcomes with these solutions," the KLAS Research analysts wrote in the report.
Generative AI refers to AI that can create text, images, or other media by learning from existing data and generating new content with similar characteristics. It utilizes generative models to understand patterns and structures in the training data, enabling it to produce novel and coherent outputs, according to KLAS' definition.
The company only surveyed 66 healthcare executives, so the survey size is rather small, but the results offer a snapshot of where healthcare leaders stand on generative AI just one year since ChatGPT debuted. The survey results offer a look at executives' perspectives on current adoption, future plans and current challenges regarding generative AI.
Many larger organizations and payers have already embraced various generative AI tools from EHR vendors, such as Epic, as well as from Google, Nuance and OpenAI.
Asked about the vendors they are currently using, healthcare executives named 3M, AWS, BastionGPT, Epic, Google, Microsoft, Nuance, OpenAI, Palantir and RapidAI.
"The release of ChatGPT sparked a conversation around how we are going to utilize AI in our organization. It has led me to pay a lot more attention to where we are using AI already as a system and to think strategically about how we can use AI to help us do our jobs," a chief medical information officer at a healthcare organization told report authors, as cited in the report.
Organizations are primarily focused on using generative AI tools to improve efficiencies in their operations, with a particular focus on documentation, patient communication and workflow.
"By leveraging generative AI, respondents hope to automate the process of generating clinical notes, summaries and reports based on patient data, thereby saving a significant amount of time," the report authors wrote.
"Generative AI can play a pivotal role in facilitating effective, personalized patient communication
by delivering tailored, timely information to patients. These solutions can also address patient queries, provide medication reminders and offer general health advice, resulting in improved patient engagement and adherence to treatment plans," the report authors said.
Organizations also can leverage generative AI has the potential to streamline workflows and operations by automating documentation, prewriting notes and templating emails.
The buzz around generative AI, and large language models in general, has reached a fever pitch as executives see the potential for the technology to improve operations. "I think it's probably the most transformative technological shift in decades. We've just leapfrogged previous technologies and companies trying to build AI solutions to automate something, and in some cases, we're watching that kind of technology be solved overnight," Justin Norden, partner at GSR Ventures, said at the HLTH 2023 conference back in April.
While healthcare organizations historically have been cautious about embracing new tech, they are eager to deploy new tools powered by generative AI. Major health systems including UC San Diego Health, UW Health in Madison, Wisconsin, Cleveland Clinic, Ochsner Health and Stanford Health Care jumped in to be early adopters of generative AI tools developed by Microsoft.
Epic also tapped Microsoft to integrate large language model tools and AI into its electronic health record software. And Oracle also is adding gen AI capabilities to its Cerner EHR. The EHR giant also integrated Nuance's Dragon Ambient eXperience (DAX) Express into its EHR workflows. Nuance is Microsoft's speech recognition subsidiary.
Telehealth company Teladoc also tapped Microsoft to integrate AI and ambient clinical documentation tech into its virtual care platform.
Google and Amazon have quickly rolled out their own generative AI models for healthcare and life sciences companies in competition with Microsoft and OpenAI, a company financially backed by Microsoft.
Startups also are developing generative AI capabilities, particularly in the area of automating clinical notes. Abridge has nabbed several notable partnerships to expand the use of its gen-AI-powered medical note-taking service. HCA Healthcare is testing out generative AI tools in ERs a part of an ongoing partnership with Google Cloud and ambient medical documentation company Augmedix.
Hippocratic AI launched out of stealth earlier this year armed with $50 million to build out what it refers to as the first LLM for healthcare with an initial focus on non-diagnostic, patient-facing applications. The company is backed by General Catalyst and Andreessen Horowitz.
Many leading healthcare players are banding together to tackle the complex issues of using AI in healthcare. UC Davis Health, along with the rest of the University of California health systems and more than 30 founding partners, launched VALID AI, which stands for Vision, Alignment, Learning, Implementation, and Dissemination of Validated Generative AI in Healthcare.
Last month, U.S. President Joe Biden issued a sweeping executive order on artificial intelligence, marking a significant move to address the accountability of how AI technology is developed and deployed.
As the industry continues to debate the promises and risks of artificial intelligence in healthcare, patients are bullish on the potential for generative AI to improve access and even lower healthcare costs.
"As more organizations start leveraging generative AI, the solutions will need to drive hoped-for outcomes and prove a strong ROI to stay relevant and viable in the market long-term," the KLAS Research report authors said.
Cost and return on investment continue to be a big challenge with implementing emerging technology. Maintaining AI infrastructure — including hardware, software, and skilled personnel — can be expensive. And, the initial investment may not yield immediate returns, making it essential for organizations to carefully assess the long-term benefits and potential cost savings, the report noted.
Healthcare executives who responded to the survey cited accuracy and reliability as the biggest hurdles to increased adoption of gen AI. "Respondents worry that inaccuracies, bias and AI hallucinations would negatively impact patients and decisions. It is also important for solutions to be proven reliable by users," the report authors wrote.
Executives also are concerned about potential issues around security and privacy. Patient data is highly sensitive and subject to strict regulations, such as HIPAA, and organizations need to protect patient privacy and ensure data security throughout the AI workflow.
"Organizations must implement robust encryption, access controls and anonymization techniques to safeguard patient information and maintain compliance with regulatory requirements," the report authors said.
KLAS intends to publish further general AI insights with the Center for Connected Medicine (CCM) in early 2024.