The potential of GenAI in health care

Episode transcript

Find episode transcript below.

IGOR BELOKRINITSKY:

00:00:00:00 Hello and welcome to the Next in Health Podcast. I'm Igor Belokrinitsky, a principal with PwC Strategy & where I get to help leading health organizations with their strategies and operating models.

00:00:15:04 And last week, we had a fascinating conversation about the possibilities that GenAI brings to pharma and life sciences industries and how it could help drive innovation and affordability and equity.

00:00:30:05 And today we will have a similar conversation about the potential of generative AI for the delivery and coverage of healthcare, so for healthcare providers and for healthcare insurers.

00:00:42:02 And so at this point, you might be asking yourself, does the world really need another podcast episode about GenAI and healthcare? And I believe it does and I'll tell you three reasons why.

00:00:54:23 First is the topic itself is a little bit unique. Every conversation that we have with health organization and health leaders out there today, they bring up GenAI unprompted.

00:01:07:06 And it's hard for me to remember the last time in the last topic that this would happen to where people just ask you about it, whatever the conversation happens to be. The second reason why this conversation will be important is that we ourselves as a firm are not just talking about it.

00:01:23:07 We're actually investing over $1,000,000,000 in developing our capabilities around GenAI and developing our people around this topic as well, and making sure that everybody's ready for the future and the final and probably most important reason to listen to this is because of the guests.

00:01:41:01 We have two great guests today. They're both returning guests to the podcast and so we have Sri Murthy. He's a director who focuses on developing growth strategies and delivering sustainable digital value transformation for payers.

00:01:54:08 And we're also excited to welcome back Inshita Wij, who's a director who focuses in digital led consumer and employee experience strategies for health systems. So, Sri and Inshita, welcome to the podcast. Thanks for being back.

INSHITA WIJ:

00:02:08:15 Thanks for having us.

SRI MURTHY GURU:

00:02:10:00 Thanks Igor. Glad to be here.

IGOR BELOKRINITSKY:

00:02:12:05 Excellent. So maybe let's begin at the beginning. Generative AI has received perhaps more than its fair share of press coverage in the past few months and so tell us about the potential you see for this unique technology in healthcare and Inshita I will start with you.

INSHITA WIJ:

00:02:31:18 We've seen a lot of technologies right in the past few years but we do think that GenAI is different given how user friendly it is? It also works with unstructured information like documents.

00:02:44:04 It has the ability to generate new interactive content and improve programmer productivity. It has the possibility to transform patient interactions and experiences with conversational AI. It can improve admin and clinical workflows.

00:03:00:14 We're also seeing cases of nurse copilots and physician copilots. So we're really excited about this technology. It's not just science fiction or hypothetical anymore. It's here right now for a variety of tasks,

00:03:14:05 and we are already seeing organizations experimenting, with GenAI, while others are ruling out or implementing larger process and workflow transformations.

IGOR BELOKRINITSKY:

00:03:25:10 That's excellent. And since you mentioning that it's not just hypothetical at this point that's already being used, it's already being implemented and generating value, I wonder if you'd give us some examples from the world of providers of health systems and physician groups of how generative AI is already being used today?

INSHITA WIJ:

00:03:44:01 Yeah, for sure. We're seeing some kind of lower risk, more immediate applications and then we're also seeing some investments in longer term applications. The more immediate ones are front office.

00:03:58:05 So patient facing and marketing or content generation based on prompts, parameters, the work that traditionally was done by your marketing agencies or even in-house teams and saving a lot of time there,

00:04:11:03 in contact centers, really end to end with human like proactive outreach to your consumers, self-service conversational, AI bots, agent assist for knowledge management and post called summarization.

00:04:27:03 So overall saving a lot of time for agents and really equipping them to have more meaningful conversations with our consumers. On the clinical or the patient services side, it's being used most immediately to reduce the documentation burden, which we all know has been a dissatisfier for our clinical staff.

00:04:47:02 So scribing, summarization, patient information look up and some hospitals are also using it to generate better handover reports and procedures between shifts. On the back office, we are seeing automation of revenue cycle processes.

00:05:02:08 You might have heard automating prior authorizations, denials and appeals management and even in IT for coding assist, HR, Legal functions for looking at company policies. Really what we're seeing is you start to implement it for one use case and other departments jump on.

00:05:20:07 And longer term, it's about providing clinicians that copilot to look up clinical protocols or more advanced even clinical decision support to suggest initial diagnosis that can be verified by physicians.

IGOR BELOKRINITSKY:

00:05:36:17 Inshita that's a great overview, really helpful and sounds like there's applications across the entire care delivery value chain, starting with documentation, interacting with producing or interrogating documents. And so let's shift gears to health insurance.

00:05:53:08 And Sri, I know you've been working for a number of years to help health insurers drive affordability of healthcare, make health insurance more user friendly, take advantage of some of the latest technology. So how does GenAI changed the game and what are some the applications you're seeing in the health insurance space?

SRI MURTHY GURU:

00:06:13:15 Thanks Igor. It's a great question. There has been tremendous interest within the payer space as it pertains to utilizing GenAI for a variety of reasons and primarily one of the points you mentioned around affordability has been a striking theme with multiple payers.

00:06:30:07 As we have seen with GenAI as well payers have been cautious on their GenAI journey so far, but there is tremendous interest. There are a lot of use cases that are being contemplated and some of them in proof of concept development across these payer organizations,

00:06:49:08 particularly as it pertains to use cases where the risk for the enterprise is low, but the business value is moderate to high and I can share a few examples here. In front office, we see payers interested in use cases such as generating RFP responses for Medicaid bids,

00:07:08:04 and generating marketing and social media content, because quite honestly, this technology does quite well with knowledge work, with creative aspects as well. In the front office, we spoke about some examples, but as you go towards the middle and back office, it becomes even more interesting.

00:07:24:05 In middle office, we are seeing use cases being contemplated around generating draft letters after processing, prior auth requests, verifying completeness and accuracy of the documentation submitted as part of provided appeals, grievances and so on.

00:07:40:06 In this way, clinicians can focus on the higher value add tasks, whereas the technology can take care of some of the more routine tasks in the back end. In the back office, which is primarily around like call centers, claims, etc., we are seeing a focus around performing contract reviews,

00:07:58:04 helping members understand their explanation of benefits, setting up copilots for claims processors and others within the back office space. The one that I find most intriguing and interesting is the idea of a copilot for a claims processor or a call center app.

00:08:16:05 Think of copilot as in the background can fetch answers for you for questions, looking through hundreds of documents in real time and really going for its recommendations on what is the next best action for this processor.

00:08:29:03 There's a lot of momentum and thought being put in trying to conceptualize what this would look like and quite honestly, like there are lot of parallels and some of these use cases to what Inshita referred on the provider side and the value drivers for these are primarily centered around efficiency gains.

00:08:45:04 That is what kind of cost savings can I get by implementing this use case? What's the productivity gain that I see? How does it help improve the effectiveness of the work that my processors do?

00:08:57:06 And taking this one step further now, payers can look beyond their own four walls. Yes, they can certainly and should implement GenAI use cases within their four walls, but also some of the leading payers already have provider enablement arms to support various physician groups.

00:09:18:02 This is another quiver in the arrow of these payers to support smaller physician groups with some of the GenAI and AI applications that Inshita had pointed out on the provider side.

IGOR BELOKRINITSKY:

00:09:30:09 That's excellent. Sri, again, a great description showing us opportunities across the entire payer value chain and then also spilling over into that very important intersection between the care and coverage between the payer and provider.

00:09:44:05 And I heard you mention this kind of a framework of the many use cases of the many uses that are possible, prioritize the ones that have high enterprise impact and low risk, and likewise as Inshita was describing all the different possibilities.

00:10:01:07 She did not talk about diagnostics. First, she talked about it last and so at some point we will do all the things that are high impact and low risk and we'll start looking at that other quadrant that has even higher impact perhaps, but also potentially higher risk.

00:10:17:29 And so I'm wondering if you would talk about how health organizations can think about the risk posed by GenAI and how they can begin to manage it for themselves and their various stakeholders, and Sri let's stick with you with health insurance and then we'll go to Inshita with the providers.

SRI MURTHY GURU:

00:10:36:17 Yeah sure Igor. So, like any new technology it is still being proven. There are a number of risks and there is a lot of work that we as a firm have done around responsible AI as well and so really the risks come to some things,

00:10:54:05 which are basic in common sense and some need to be thought through with the right sort of framework and approaches. For example, like patient data always needs to be handled with care. You want to make sure the right protocols are put in place there.

00:11:07:04 But as you think about deploying some of the use cases within your environment that are security and IP risks, so for example, you want to make sure that the data that you are using to train the model is not going out to the external world and it is contained within the four walls of your organization.

00:11:26:29 You want to make sure that whatever outputs come off, there is an algorithm risk that needs to be managed in terms of understanding the bias, the explainability and the fairness. Explainability is a major concern.

00:11:40:04 And then there are darts not only around managing the risks from external perception risks, algorithm risks and explainability, but also financially you want to make sure that any sort of use case that you are going to go build,

00:11:54:08 there is financial discipline and rigor; meaning is their real ROI for these use cases. Is the juice worth the squeeze? And over time, the cost of building the proof of concept and productionalizing this in your environment will become cheaper.

00:12:11:05 But at this stage, it's worth investigating a little bit more on the financial aspect as you go build the use cases.

INSHITA WIJ:

00:12:19:09 Yeah, great points there Sri and I think all of what you said applies across industry, not only to health system, I would say any industry that's taking on GenAI use cases or developing a strategy.

00:12:33:07 I also want to say, according to PwC’s Trust Survey of 500 business executives, nearly all of them said that they are prioritizing at least one initiative related to AI systems in the near term,

00:12:48:04 but only 35% say that they will focus on improving the governance of AI systems in the next 12 months. So that's an important point to mitigate the enterprise risk that she highlighted, organizations should focus on establishing a very clear governance at different levels in the organization.

00:13:07:05 So at the top or executive level, thinking about just your culture, embedding the ethics, the boundaries of AI and involving your entire organization into the risk and ethics of AI,

00:13:22:06 and governance for selecting and implementing the use cases at the functional level and making sure it has participation not just from IT or digital, but really involving clinical compliance, legal operations and HR.

00:13:38:03 We're seeing organizations think about different operating models for this AI strategy and implementation such as enterprise level committees, decentralized functional led AI committees, or even Me trust kind of some form of the combination of these right to ensure the right oversight.

00:13:58:01 And I would maybe end with saying that it's also imperative to make sure we upskill and train employees and involve them and thinking about the risks and rewards of GenAI that should not be an afterthought.

IGOR BELOKRINITSKY:

00:14:11:07 Thanks Inshita that’s a great point and a great reminder, and I know you in particular work a lot on improving the employee and the caregiver experience in healthcare, and this technology has the potential to further improve it, but also bring some risks and so very important to consider that aspect and appreciate that reminder.

00:14:31:08 Thank you both for great conversation and for simplifying and clarifying for us what this technology is, what it's good for, what its potential is for both payers and providers to drive efficiency,

00:14:48:05 to drive experience, to drive better results for all of their stakeholders involved and also for helping us see that we're still in the early days and that all the uses and all the risks are still being discovered and identified,

00:15:06:02 and the important thing to do at this point is to educate yourself about the possibility of the technology and to start putting structures in place to use it responsibly. So thanks for the great conversation.

INSHITA WIJ:

00:15:18:14 Thank you. It's really an exciting topic.

SRI MURTHY GURU:

00:15:21:03 Thank you for having me Igor, really appreciate it. Passionate about this topic and looking forward to more conversations on this.

IGOR BELOKRINITSKY:

00:15:26:24 Oh yes. We'll definitely have both of you back to talk about this in the future. For more on these topics and other health industry insights driven by policy, innovation and care delivery changes, please be sure to subscribe to our podcast.

00:15:40:08 So that you can get all the great future episodes as well as listen to the past episodes. Until next time, this has been Next in Health.

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