In the future, experts could point to a single tipping point in healthcare’s adoption of artificial intelligence (AI). And it’s about to start right now.
In a survey from Healthcare Dive and Microsoft that polled 130 healthcare executives, respondents said that specific AI use cases could see a dramatic increase from now to 2026. These functions haven’t yet seen their AI heyday, but they could very soon.
In particular, clinical documentation is one function highly likely to see near-term growth in AI uptake: 42% of executives said they planned to implement an AI tool for that use by 2026, compared with 10% who use it right now for that purpose.
This is an increase of 320% — an extreme jump, to be sure. But it also points to something more profound: a “part two” in AI’s adoption story for healthcare systems. And for a care ecosystem embattled by financial and labor pains, this next generation of AI use cases could add new value in the nick of time.
What’s behind this shift?
The line in the sand between current and future AI use cases comes down to brass tacks. Initially, AI’s entry point into healthcare systems involved activities directly linked to revenue capture: scheduling, check-ins and coding. At 40%, 40% and 31%, respectively, these were the functions that saw the highest rate of already implemented AI solutions, according to the survey.
But once leaders check off those priorities, they can expand and experiment in other areas, the survey found. This is evidenced by the fact that not only clinical documentation went up from 10% to 42% but certain other areas did, too, including clinical decision support (from 8% to 39%) and patient education/engagement (from 2% to 33%).
“Understandably, leaders initially want to implement solutions where the healthcare dollars are,” said Jared Pelo, Chief Medical Information Officer at Microsoft, in the survey report. “If someone doesn’t schedule or check in with you, or you don’t code them, there is no money. But once those priorities are addressed, you can then invest more in those other areas, including clinician and patient experience.”
Thus, this “part two” of AI adoption is marked by an increasing pull toward automation to address areas that have been historically problematic — difficult to address and difficult to quantify — such as patient and clinician satisfaction, he added.
Getting healthcare where it needs to be
It’s unsurprising that clinical documentation jumped so measurably. With AI assistance, physicians can focus on the patient while ambient technology documents the encounter. Already, early adopters have demonstrated that value: For example, when Stanford Health Care clinicians deployed an AI assistant for clinical documentation, nearly all the physicians — 96% — said it was easy to use. Roughly 2 in 3 said it saved time.
That has benefits all around, Pelo noted. Patients can get more face time with their physicians, clinicians can get less screen fatigue and hospitals can capture more value from an improved care-delivery continuum.
“We see this consumerization of healthcare coming — it isn’t here yet, but it’s coming,” he said. “Right now, you don’t often come out of a healthcare appointment and say, ‘Wow, that was an amazing experience. I can’t wait to go back.’ But we’re getting there. And these technologies are going to help with that transition — to help consumerize healthcare to improve engagement, clinician satisfaction and patient satisfaction.”
The future of AI is contextualized and seamless
Even though specific functions such as clinical documentation are on track for rapid growth, the real undertone of healthcare AI’s “part two” is orchestration. That is, future AI won’t be measured by a use case here and a use case there — it’ll be contextualized into the workflow more seamlessly and intuitively as a whole.
In this setting, AI becomes a multidimensional resource shared by everyone: Multiple agents can be used in multiple ways, with the doctor-patient visit informing everything. This is the ethos of Microsoft’s new Dragon Copilot solution, which is the first AI assistant for clinical workflow that brings together the trusted natural language voice dictation capabilities of DMO with the ambient listening capabilities of DAX, fine-tuned generative AI and healthcare-adapted safeguards.
Clinicians will benefit from Dragon Copilots’ fast, accurate, secure and intuitive speech and ambient capabilities to document care, navigate electronic health record (EHR) workflows, and perform other administrative tasks. To learn more about this solution, visit https://www.microsoft.com/en-us/health-solutions/clinical-workflow/dragon-copilot.
