Kyndryl has allied with Microsoft to apply generative artificial intelligence (AI) to health care using Microsoft Dragon Copilot, a voice-enabled assistant designed for clinicians to help collect data without having to enter it manually.
The goal is to automate documentation workflows in a way that enables health care professionals to spend more time caring for patients, says Trent Sanders, vice president for U.S. health care and life sciences at Kyndryl.
Health care professionals, for example, will be able to take advantage of ambient listening to summarize notes, prepare orders and draft after-visit summaries as part of a larger effort to leverage AI to reduce health care costs, he adds.
Kyndryl is committing to making available a team of experts to provide support and implementation services to health care organizations looking to integrate Microsoft Dragon Copilot into existing workflows like virtual nursing service, says Sanders.
Business benefits will include not only a reduction in errors but also more accurate billing for the services delivered, he adds. Many health care organizations today operate on razor-thin margins that force them to ensure they are billing for every service provided to keep their doors open, notes Sanders.
Of course, there may also come a day when AI reduces the cost of delivering those services to the point where these organizations can more easily remain profitable.
Regardless of the outcome, most health care providers do not want to have to choose between patient care and completing paperwork in their off hours, says Sanders. AI technologies provide an opportunity to regain some work-life balance for many health care professionals, he adds.
It’s not clear how pervasively AI technologies are being adopted but a Kyndryl survey notes that while 86% of business and IT leaders in the health care sector feel their AI implementations are best in class, only 42% have seen a positive return on those investments.
Achieving that goal may simply require more time. Just about every organization is experimenting with multiple AI use cases but in a health care field where there is a chronic shortage of skill and expertise, the opportunities to leverage AI are plentiful. As the overall population continues to skew toward older individuals, the number of people that will need those services is only going to increase, while the number of people available to fill those roles stays comparatively steady.
In fact, a recent report from the World Economic Forum (WEF) is urging rapid adoption of AI to improve health care. For example, AI can already detect early signs of more than 1,000 diseases in addition to interpreting brain scans twice as accurately as a health care professional.
Unfortunately, there is still a wide AI adoption gap, with the report noting that in the U.S. only one in 1,850 job listings requires AI skills.
The goal when it comes to health care should also be to provide a better outcome for the patients, but if there are not enough trained individuals to provide those services, that next best option is clearly going to be a machine that in addition to never getting tired is always available.
