Increasing productivity in healthcare: An interview with Allen Karp of Horizon Blue Cross Blue Shield
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What is the main topic discussed in this episode?
McKinsey on Healthcare, a podcast series about visionaries, leaders, and problem solvers shaping the future of healthcare. Good afternoon.
This is David Knott. I'm a senior partner in McKinsey's Healthcare Practice, and today it is my pleasure to have Alan Karp, Executive Vice President of Healthcare Management and Transformation at Horizon Blue Cross Blue Shield, join me for a conversation around productivity in healthcare. Alan, welcome, and thanks for joining us.
Thank you, David.
Alan, perhaps just to start, I think at the highest level we have seen the application of technology and other measures that improve the productivity of industries over time. I think one of the vexing challenges in healthcare is that we continue to throw a lot of technology at various problems and yet we see precious, if any, improvement in productivity over time. And we all know that affordable quality is one of America's greatest challenges. Any top-of-mind observations on why this is such a vaccine problem so entrenched for healthcare?
Yes, and that's a great question, David. I will focus on two that I think drive the fact that our productivity in healthcare is not as great as some other industries. One is the economic model historically has been a fee-for-service system. based model where incentives are not aligned between payers and providers. And there are significant administrative processes that are in play today as a payer interacts with a provider, and that causes inefficiencies. The other area would be within a health system, for example, the administrative and operational processes are cumbersome. and inefficient. If you look at the healthcare industry, it is a very labor-intensive industry, which of course drives the cost up and creates some of this inefficiency.
There was a study done by Johns Hopkins where they were looking at two areas of focus. One was the way they assigned beds to patients who came into the hospital, and the second was how quickly they can assign beds to those who came through the emergency room. Utilizing AI and machine learning, they were able to reduce the amount of time it took to assign beds by 30%. And they were able to cut the wait time for those members who came in through the emergency room, or those patients, I should say, through the emergency room by 20%. So that one example of using technology to focus on those areas that are cumbersome and improve inefficient processes.
It sounds like one of the most fundamental issues is the alignment of the economic incentives. And so you've talked a little bit about fee-for-service environment and then the types of operating models that have evolved over time. Are there ways that you see today steps or progress being made where we can actually start to make some of these changes?
There are still barriers that exist today. However, I have seen significant change, which I believe will improve productivity significantly as we move forward. As we change the economic model and we align the incentives with hospitals and physicians, the administrative processes that we have in place today, such as pre-authorization or concurrent review, are either reduced or they go away. Because now, by moving the value base, we're passing some of the financial risk to those providers, along with the tools necessary to manage that risk. And therefore, we can eliminate some of those processes, which will lower costs and provide a much more efficient flow for the patients and for our members. The other area would be on our side, being a payer, using the AI machine learning technology to be able to identify those pre-authorizations, for example, that are overturned a significant portion of the time.
How does technology impact productivity in healthcare?
So we could teach the machine how to look for those. And then when a provider calls in for a pre-authorization, they would be able to get that pre-authorization on an automated basis. Now that allows our nurses to focus on those clinical conditions that are either in a gray area or not yet supported by the evidence and makes the whole process much more efficient.
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Chapters
5 chapters
1
What is the main topic discussed in this episode?
0:07–4:19
2
How does technology impact productivity in healthcare?
4:19–10:12
3
What are the challenges of the fee-for-service model?
10:12–18:21
4
How can AI improve operational efficiency in healthcare?
18:21–23:21
5
What steps are being taken to align incentives in healthcare?
23:21–28:41
Speakers
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