Dive Brief:
- Relatively few healthcare organizations currently use generative artificial intelligence tools, but more than half are looking to implement or buy these products within the next year, according to a survey by Klas Research.
- Operational efficiency is the biggest opportunity for generative AI in the sector, according to healthcare executives. Many didn’t know yet where they’d use the burgeoning technology in their companies, but respondents with a strategy in place pointed to AI use in documentation, patient communication, workflow automation and revenue cycle management and coding.
- Still, surveyed executives reported some concerns about generative AI. Accuracy and reliability topped the list of challenges, which was mentioned more than twice as much as other concerns like cost, return on investment, and security and privacy.
Dive Insight:
Generative AI, which can create new content like text or images, became a hot topic in healthcare this year as tech giants like Microsoft, Oracle, Amazon and Google revealed their own products geared toward the industry.
Many generative AI tools for the sector focused on reducing clinicians’ numerous administrative tasks, like note taking and documenting patient information in an electronic health record. Providers have long reported spending hours working in their EHRs, sometimes after work, and potentially fueling burnout.
The latest Klas report found just a quarter of the 66 executives interviewed had already implemented generative AI, and many said it was still too early to determine outcomes.
Larger organizations, which often have a greaten number of resources, were more likely to have already adopted the tools. Bigger companies often have more data readily available, and they can more easily employ data scientists to develop and implement the tools, the report’s authors noted.
Executives from those larger organizations were also more likely to purchase or implement generative AI products soon. Overall, 58% said their company was likely to buy or implement the tools within the next year.
But some experts have raised concerns about rapid uptake of generative AI in healthcare, noting some models’ tendency to hallucinate and make up information. There’s also the potential for bias to exacerbate healthcare inequities and questions remain about who is accountable for errors.
The Klas survey found 21 out of 45 executives rated accuracy and reliability as the biggest challenge for integrating generative AI in healthcare.
Nine leaders pointed to cost and return on investment as the biggest challenge. Setting up and maintaining the infrastructure can be pricey, and the investment may not immediately bring returns — highlighting the importance of carefully assessing the long-term benefits, the report noted.
