Health systems lag on AI strategy
Generative AI can help health systems improve margins, but only 6% of them have a strategy ready, according to a recent report from Bain & Co.
Why it matters: The hospital sector is seeing its most challenging year since 2020, with many systems buckling under wage inflation and staffing shortages.
What's happening: Most health systems are eyeing near-term generative AI applications such as improving clinical documentation, structuring and analyzing patient data, and optimizing workflows.
- For example, the University of Kansas Health System recently partnered with generative AI platform Abridge to reduce documentation burden.
What's next: Hospitals hope to start using generative AI for predictive analytics, clinical decisions and care recommendations.
What they're saying: "It's time to play offense — or be forced to play defense later," write Bain partners and lead authors Eric Berger and Margaret Dries.
- "Choosing from the laundry list of generative AI applications is daunting," they add, noting companies risk "overinvesting in the wrong opportunities and underinvesting in the right ones."
Be smart: Amid a noisy generative AI market, focus and prioritization are persistent challenges for health systems, the report notes.
- "In many boardrooms, executives are debating overwhelming lists of potential generative AI investments, only to deem them incomplete or outdated given the dizzying pace of innovation," Berger and Dries write.
- Hospitals should start small, piloting low-risk generative AI applications with a narrow focus, such as billing or scheduling, the report suggests.
- Health systems should also be weighing a buy-build-partner strategy when it comes to generative AI.
The bottom line: While "a wait-and-see approach is a tempting prospect," health systems shouldn't rest on their laurels when it comes to implementing new AI.