While Covid-19 may no longer be dominating the global news cycle, healthcare providers and payers are still feeling its reverberations. More than half of US hospitals ended 2022 with a negative margin, marking the most difficult financial year since the start of the pandemic.
CEOs and CFOs remember the challenges all too well: The Omicron surge halted nonurgent procedures in the first half of the year, government support tapered off, and labor expenses ballooned amid staffing shortages. There was also the record-high inflation that continues to intensify margin pressures today. According to a recent Bain survey of health system executives, 60% cite rising costs as their greatest concern.
Payers and providers are now on the hunt for margin improvements. In our experience, the most successful companies won’t merely reduce costs, but also ramp up productivity. When done right, modest technology investments can accomplish both.
Artificial intelligence (AI) may hold part of the answer. With the costs to train a system down 1,000-fold since 2017, AI provides an arsenal of new productivity-enhancing tools at a low investment.
Many executives recognize the growing opportunity, especially with the recent rise of generative AI, which uses sophisticated large language models (LLMs) to create original text, images, and other content. It’s inspiring an explosion of ideas around use cases, from reviewing medical records for accuracy to making diagnoses and treatment recommendations.
Our survey reveals that 75% of health system executives believe generative AI has reached a turning point in its ability to reshape the industry. However, only 6% have an established generative AI strategy.
It’s time to play offense—or be forced to play defense later. But choosing from the laundry list of generative AI applications is daunting. Companies are at high risk of overinvesting in the wrong opportunities and underinvesting in the right ones, undermining future profitability, growth, and value creation. A wait-and-see approach is a tempting prospect.
However, we believe the next generation of leading healthcare companies will start today, with highly focused, low-risk use cases that boost productivity and cost efficiency. Over the next three to nine months, these companies will improve margins and learn how to implement a generative AI strategy, building up the funds and experience needed to invest in a more transformative vision.
Endless potential—and high hurdles
The excitement around generative AI may feel akin to the hype around other recent digital and technology developments that never quite rose to their promised potential. Well-intentioned, well-informed individuals are debating how much change will truly materialize in the next few years. While developments over the past six months have been a testament to the breakneck speed of change, nobody can accurately predict what the next six months, year, or decade will look like. Will new players emerge? Will we rely on different LLMs for different use cases, or will one dominate the landscape?
Despite the uncertainty, generative AI already has the power to alleviate some of providers’ biggest woes, which include rising costs and high inflation, clinician shortages, and physician burnout. Quick relief is critical, considering that the heightened risk of a recession will only compound margin pressures, and the US could be short 40,800 to 104,900 physicians by 2030, according to the Association of American Medical Colleges.
Many health systems are eyeing imminent opportunities to reduce administrative burdens and enhance operational efficiency. They rank improving clinical documentation, structuring and analyzing patient data, and optimizing workflows as their top three priorities (see Figure 1).