FRESH TAKES ON BIG IDEAS

AI has been used in healthcare for a while now, often in ways that patients don’t see. For example, AI is used to optimize a hospital’s workforce and inventory, making sure the facility is properly staffed and supplied. However, McKinsey research reveals that the healthcare field is behind most other industries in adopting AI. It’s a very fragmented industry, with tons of hospitals. And the systems that have been used in those hospitals have tended to be bespoke, which makes it difficult to copy innovations specific to one care setting and paste them to another. Another issue has been data, which has been siloed within hospital walls and has not been transferable to other hospitals.

But generative AI (gen AI) changes several dynamics. Large language models are applicable for many, though not all, use cases. This is a paradigm shift because it allows developers to focus on making an existing algorithm work as opposed to creating the algorithm in the first place. If most of your time is spent getting an off-the-shelf algorithm to work better, you can turn your attention to the quality of your data, getting more data, and making sure that users adopt gen AI. I think that’s where we’re seeing a lot of focus, which is pretty exciting in being able to unlock value.

Here’s one example. In hospitals, data is contained in electronic medical records. This might be data from devices like implants or scans like MRIs and ultrasounds, or it might be data about prior encounters that patients have had in other hospital systems. There are third parties thinking about how we can anonymize, or “tokenize,” all this data so that it can be shared across hospital walls. One use would be to improve clinical trials by making it easier to find the patients who would be most likely to benefit from a particular trial. My prediction is that we’re going to go beyond improving operational tasks and start seeing gen AI used to support clinical decisions, which, up to now, we haven’t seen so much. That said, it will be essential to keep a human in the loop, since the technology can “hallucinate” and will need to be monitored.

“My prediction is that we’re going to go beyond improving operational tasks and start seeing gen AI used to support clinical decisions.”

What will this look like for healthcare consumers? You might notice that during an appointment, physicians now look you in the eye the entire time that they are talking to you as opposed to typing on a keyboard for part of it because the visit is being documented automatically. Or you might have less friction when scheduling appointments because you will no longer need to call the front office and wait for them to find a slot that works for you. Instead, it could be much more like talking to an automated system, doing the back-and-forth the way you might interact with ChatGPT. For clinical questions, right now, you have to wait to talk to a human, and we all know that it can be hard to get your physician on the phone if you don’t have a scheduled appointment. I believe that gen AI may be able to point you toward the right sources of information. Eventually, you may talk to a human, but before that happens, gen AI could potentially help patients with quite a bit. It could be like everyone having a doctor in their family, which would democratize the flow of information that gets to patients.

Will it make the population healthier? I’m an optimist, so I think that it will. There is plenty of data showing that one thing that gets in the way of good care is the ability to make fast, informed decisions. Another is ensuring that patients actually show up for and follow through on their treatment. My hope is that we develop a way for gen AI to interact with patients that helps them understand their treatments.
 
Of course, all of this depends on whether the technology is embraced, especially by healthcare providers. And right now, I think that many see it as a threat or yet another complicated thing to learn. Many people would just rather keep their existing workflows and not have to deal with these kinds of changes. But if they see the value in either saving time or taking away bothersome or onerous tasks, they will start to adopt it. There’s a phrase that I really like: gen AI doesn’t have a technology issue; gen AI has a design issue. The technology generally works pretty well. But now we need design folks to think more about what it will take for the healthcare industry to adopt it. When these systems are well designed, with users in mind, that’s when you’ll see it take off.

ABOUT THIS AUTHOR

Delphine Nain Zurkiya is a senior partner in McKinsey’s Boston office.