The importance of network effects, role of big tech, and the future of health IT
Platform business models from big tech are beginning to demonstrate their relevance in healthcare and challenge the traditional, linear value creation form of business model.
Many view EHRs as likely incumbent candidates for platforms, however we may see more activity from virtual care platforms and collaborative platforms composed of health systems.
Mergers and acquisitions (M&A) are often a key component of platform business models – though not always (ie Epic) – and the use of AI as a central component of digital transformation is becoming more standardized.
In recent years we have seen a great deal of speculation about how the big tech players such as Amazon, Google, Apple and Microsoft would bring their platform business models to healthcare and disrupt business as usual. This has proven to be a more difficult hill to climb than expected, but the platform business model goes well beyond the platform natives in big tech. In a podcast with Vince Kuraitis and Randy Williams, we explored the nature of platform business models, how they differ from traditional business models and how they may impact the future of healthcare.
Traditional business models create products and services through production side integration that are delivered in a linear value creation process. Value capture is through optimization of production and the focus is on owning the supply chain. Gatekeepers are common and consumers experience friction when trying to access services. Rapid Covid tests are a great example in healthcare because they are developed manufactured and distributed by producers while consumers must go through gatekeepers to access.
Platform business models unlock new sources of value both on the creation side of the transaction, but also on the consumption side. Their function is to facilitate matches and consummate exchanges of goods/ services, thereby creating value for all parties. Platforms are usually less constrained by owned inventory. Often by using data and digital tools, platforms improve customer experience by increasing access to products, matching preferences, increasing convenience, and eliminating gatekeepers.
Most importantly, platforms all have in common a reliance on network effects, meaning, the more participants who join the platform, the more value is created for all other participants. This can take the form of better discovery or matching algorithms, or increased choice/ competition, and increased access to customers.
Healthcare is a classic pipeline business where producers of services (think providers of care) are constrained by gatekeepers, ie. practice managers or health plan network contracts. Consumers are likewise constrained by an inefficient market that does not have to meet consumer demands for access, affordability, convenience, or individual preference. Platform businesses see these inefficiencies and consumer frustrations as low hanging fruit, and are applying increasing competitive pressure to traditional healthcare entities. Adapt or continue to be displaced.
Incumbents as Platforms: EHRs and the Rise of Telehealth Platforms
In healthcare there is a tendency to think about platforms as technology, but this is limiting. It is important to think about how EHRs were built around physician workflows and have been viewed as a retrospective patient record in general. Vince Kuraitis argues that a good exercise is to think about what they would look like had they espoused platform thinking a long time ago. Rather than controlling data flows and limiting integration they would have acquired critical capabilities to configure themselves as more prospective, analytical tools with greatly enhanced integration with other IT vendors and services.
Platforms create ecosystems in part through acquisitions and enabling app economies to grow on the platform itself. These can extend the range of services offered to attract new users, and new users attract more sellers. If we compare acquisitions by Google (246) and Microsoft (224) with Epic (0) and Cerner (17) we see a stark difference in mindsets for how they think about innovation and creating ecosystems that enhance user experience. The Epic app store has about 570 apps, Cerner approximately 100 as compared to the Apple store with 350,000 apps (but unwieldy to navigate). This reflects the shift in mindset from a business of software to a platform as a marketplace.
Virtual Care as Platform. Vince and Randy both spoke about the growing role for virtual care platforms and how they should be viewed as platform natives within healthcare. They are evidence of a growing ecosystem that circumvents the EHRs and attempt to provide care outside of the traditional healthcare system. In fact the recent presentation of Teledoc’s CEO at JP Morgan’s health conference demonstrated their goal to become a virtually integrated care platform.
A number of companies have emerged that will facilitate this parallel healthcare universe of platforms. Zus Health explicitly takes on data blockers (eg. EHRs and HCOs) with tools that can help build better digital health experiences. Wheel provides the people, technology and support to build virtual care capabilities. Redox focuses on payer interoperability and virtual care integration capabilities for providers. These are examples of focused platform enablers.
A number of collaborative platforms such as Graphite Health and Truveta have been created in recent years that are typically backed by a consortium of health systems ranging from 4-20 different systems. The realization that any given health system lacks the scale to compete with big tech platforms is driving collaboration across health systems. They are driving faster interoperability with the goal of navigating the growing thicket of apps for patients and providers that has become unwieldy. We may see more of this type of platform in the future.
AI’s Role in Platform Business Models
Digitization of healthcare data is well underway compared to a decade ago. The digital infrastructure is largely laid down. We are now seeing entities use this abundance of data to go to the next logical level…analytics. In the middle of the last decade, the use of GPUs created the opportunity more efficiently power machine learning and neural networks.
Healthcare often involves creation or use of a set of structured and unstructured data. While much of healthcare data still sits in unstructured siloes, more and more structured data is beginning to power AI solutions and improvements to human processes. With the increase in computing power, one of the first targets has been images, both radiographic, and pathology images. AI is already proving to be more accurate than a radiologist alone in diagnosing some types of tumors like breast cancer.
Competitive advantage increasingly comes from advantages powered by data. As platforms collect more data about patients and services, for example, they can build better models to match consumers with products and services. This describes the central role AI has played for Amazon in other sectors. But as AI advances, the traditional gatekeeper/ expertise of the physician may be increasingly challenged, not in the clinical judgement sense, but in access to wellness or prevention services or goods.
This type of dynamic is already at play in the area of precision medicine and connecting patients to clinical trials, for example. Consumer trust will be an issue, as will data rights. Will consumers “trust” machines to “diagnose” their illness? A big question. We will more likely see AI deployed to augment human intelligence in the clinic and more RPA use for administrative functions to reduce friction.
Conclusion: Megatrends and the Future of Healthcare Platforms
A number of trends will be driving the platformification of healthcare over the next decade and beyond:
- Consumerization of healthcare will accelerate demands for access, pricing transparency and affordability, convenience, and preference matching, best met by platform strategies.
- Digitization of healthcare into structured datasets will accelerate use cases for AI, further displacing gatekeepers. Capturing data directly from consumers through devices, and home technologies could further displace dependency on providers as data gatekeepers.
- Data fluidity will likely become the ultimate platform battleground. Once “unlocked” and fluid across entities and systems, data will accelerate platforming strategies and opportunities to disrupt traditional healthcare business models.
- Incumbents will see pressure from all sides: from outsiders who are platform natives, from investor backed entities looking to disrupt the traditional models, and from each other as some incumbents adopt platform strategies to open new markets and access new consumers. Many will have in common a “consumer first” business model.
Hybrid models are and will emerge as incumbents respond to market pressures. In our conclusion Vince and Randy discussed the potential for mega-platforms as we have seen in other sectors and what are the possibilities for healthcare. A good place to look is in China with the platform PingAn Group. They focus on the intersection of fintech and health tech to provide a wide range of services on their platform. In the US healthcare context, our guests view United, Anthem and Kaiser with their substantial virtual care capabilities as candidates to progressively grow through mergers and acquisitions towards a PingAn-like type of platform in the future.
Read the AI-generated transcript below:
Randy Williams: [00:00:00] Another one that we’ve talked about earlier is the digitization of health care into structured data sets. And again, this is going to continue to accelerate the use cases for artificial intelligence and likely displace gatekeepers as the information that comes from that artificial intelligence approach begins to replace some of the knowledge expertise that health care providers traditionally have been able to protect.
Liz Hughes: [00:00:28] Welcome back to a fireside chat with Chilmark Research; looking at health care I.T. with a lens to the future.
Jody Ranck: [00:00:38] Hello and welcome to the Chilmark Research Health IT podcast. I’m Jody Ranck. I’m a senior analyst with Chilmark Research, and today I’ll be speaking with Vince Kuraitis and Randy Williams, who are going to talk to us about platforms in health care. And to get started I’d like Vince and Randy to introduce themselves, and we can jump right in on our discussion.
Vince Kuraitis: [00:01:03] Okay. That’s correct. I have been around health care for over 30 years and for the last 20 plus years, I’ve been running my own health care consulting company. Better Health Technologies work with clients around business model strategy partnerships. My My Journey down the platform Rabbit Hole began in 2007, when a client asked me, Is there anything around these Google, Facebook, Amazon models that can apply in health care? That was Randy Williams, who’s also our CO guest today, Dr. Randy Williams and Randy and I kept in touch. We’re writing a book on health care platforms and very much appreciate the chance to be with you today.
Jody Ranck: [00:01:53] Thank you, Vince. And Randy, provide a little intro.
Randy Williams: [00:01:57] Hi, Jody, I’m Randy Williams. As Vince mentioned, we go back a ways I don’t think I have quite 30 years of experience, but starting to get close to it. I’m a physician by background and a serial entrepreneur have spent the last 15 or 20 years building and scaling health care technology related companies and entities. And over the last three years have been working on platform based consulting business strategy, consulting through my consulting organization called Digital Care Advisors, and looking forward to talking about the topic with the two of you today.
Jody Ranck: [00:02:31] Great. Well, thank you, Vincent Randy. So I just want to jump right in and to sort of set the playing field a little bit. I thought it’d be good to just begin with some of the basic concepts and vocabulary around platform business models and how they contrast with traditional business models. So if you could maybe sort of set the playing field for us, so to speak on that front for folks that don’t have a background on platform economies and business models.
Randy Williams: [00:03:01] Well, I’ll take a stab at that. You know, traditional business models really produce products and services, and they do that through, you know, taking the production side, integrating that and ultimately selling and delivering a product or a service to a customer. So it’s a kind of fairly linear value creation process, and those traditional businesses are designed to capture value by optimizing production. Therefore, they tend to look at either owning or at least controlling their supply chain. And in order to get access to those products, consumers or customers are often forced to go through a gatekeeper, somebody that might give them access to those products or match their needs and interests with the availability of those products. And as you can imagine, that introduces its own friction. And so I like to give an example of a health care pipeline business, as it would be called one that you all are familiar with these days. Things like rapid COVID tests, which are developed and manufactured and ultimately distributed by producers who then tend to capture the value for themselves. While the consumer has to go through a bunch of hoops, sometimes through gatekeepers, in order to access those and platform businesses really contrast with these traditional pipeline businesses by unlocking new sources of value both on the creation side of a transaction but also on the consumption side. Their function is really to facilitate matches or to consummate exchanges of goods and services, thereby creating value for all the parties. And oftentimes they’re using data or digital tools to facilitate and improve a customer experience by increasing access to those products, maybe by matching their preferences and ultimately increasing convenience and sometimes even eliminating the role of the gatekeeper.
Jody Ranck: [00:04:55] And Vince, a quick question for you, because I know we’ve spoken about this in the past. We hear a lot of talk about network effects in these discussion of platforms as wonder if you could just give us a quick overview of how those work as part of what Randy just spoke about.
Vince Kuraitis: [00:05:11] We find that in health care, a lot of folks think about platforms as technology, and that’s not inaccurate, but it’s limiting. And really, the sine que non of platform business strategy and business models is to understand and create network effects. The basic idea being as Facebook as an example, you have more value created in the platform, the more of your friends join. There’s also indirect network effects, which might be illustrated by the Apple iOS and Google Android. It’s because those platforms have two million plus apps that you are drawn to those platforms, and it creates a flywheel effect. The more developers that you have on Android and iOS, the more people are attracted, the more people are attracted, the more developers you get. That’s really what you’re trying to create in with the network effect
Jody Ranck: [00:06:14] Rate, I see. So when we raise the issue of platforms in health care, everyone immediately begins thinking of Amazon, Apple, Microsoft, the Big Tech players coming into health care. And here are a lot of talk how they’re going to disrupt health care. But we’ve yet to see that exactly. And so before we get into sort of the Big Tech traditional platform players we want to go into, if we could have a discussion about the incumbents and there we tend to think about the EHR players in the market and what should we be thinking about in terms of platform specific to health care and the potential for some of these large EHR players to become platform players that could compete indirectly or directly with the Big Tech players as they encroach upon health care?
Vince Kuraitis: [00:07:06] So my characterization is EHR are the poster child for a lack of platform thinking in health care, and I’m going to try and put this in a positive spin. I’m going to tick off a few points about what the right mindset would have been had the large duopoly of EHR been thinking like platform businesses think first. We’ve been hearing about EHR 2.0 for over a decade, the EHR that’s built around clinician workflows. That’s more than just a record retrospectively. It’s a plan prospectively, and we don’t focus simply on transactions. We focus about intelligence and data flows. Secondly, the platform thinking would have said we. Fire critical capabilities to maximize innovation and integration. Google, for example, is acquired 233 companies. Microsoft has acquired 224. How many has Epic acquired? The answer is zero. To their credit, Cerner has acquired 17 companies and as something of a Segway, maybe for later. Wouldn’t it have been a lot more interesting and potential for innovation at Cerner, not been acquired by a company that’s just cutting its teeth? What if it had been acquired by Apple or Microsoft or Google that has a significant presence in health care? The third thing about platform thinking in EHR is the mindset would have been we’re going to turbocharge an ecosystem of third party developers. The reference I made earlier to Apple and iOS, or rather Google Android having two million plus apps.
Vince Kuraitis: [00:09:01] So you look in the App Store with Epic and they’ve got 572. As of my last count, Epic or Cerner has about 100. And is that a lot or a little? Well, they’ve been very late. They came into the App Store arena about 2017 and compare 500 apps even to three hundred and fifty thousand mHealth applications that are out there. We know there are 1500 light companies, there are thousands of digital health companies. I think that could have made a much more significant effort. Or as my colleague Seth Joseph would have described it. You think of yourself not as software, but you think of yourself as a marketplace. And the last point I’ll make is that they would have thought about maximizing interoperability instead of what we’ve seen really is foot dragging over the last decade. You know, the fact of the value of data and that health care is inevitably moving to value based care payment. It’s been obvious for for quite a while. And in turn, I think platforms the EHR platform could have had a much broader role than they’re destined to have had. They had that sort of mindset much earlier to siRNAs credit to Dr. Feinstein. I think he’s trying to create the most interoperable EHR. That’s that’s a good example of platform thinking.
Jody Ranck: [00:10:41] Not great. Randy, do you have anything you want to add to that?
Randy Williams: [00:10:45] Well, I think Vince has captured the essence. I would just probably add that, you know, to their credit, EHR by and large are responsible for the the biggest chunk of the digitization of health care data that’s already been underway for over a decade. And I think what we’re seeing is that it’s time to move beyond just the digitization of that infrastructure, to be able to use that infrastructure for data to flow and for value to be created and captured across the ecosystem.
Jody Ranck: [00:11:12] And that’s a good segue way into our next question around the role of AI in all of this and we think about. You know, there’s a lot of talk about digital transformation at the moment, and AI is an important component of that. So what you just spoke about, Randy, that speaks to a lot of what how we think about the role of AI in the overall digital transformation beyond just AI applications as point solutions. So what are your what’s your take on the role of AI in these platform economies and business models? Just how do you see that playing out in health care?
Randy Williams: [00:11:51] Well, I think A.I. is really probably the next frontier of digital platform transformation in health care, to be honest. One of the reasons for that, as I mentioned, is that the digital infrastructure is largely already been laid. We’re starting to see a lot of structured data within the health care domain, and that first level of activity around digitizing and structuring data is critical for AI to then come in as the next layer in the evolution, largely when people have that kind of massive data. The next logical thing to do is to start to analyze it and turn that data into new insights and predictive information, for example. And that’s where AI comes in and exerts its power and influence over the last decade. You know, it’s really been the growth of computing power that’s allowed this analytic capability to turn to such techniques as machine learning and neural networks and deep learning to be able to not just write analytic algorithms, but to be able to actually see those algorithms themselves learn and improve over time. And that’s actually a network effect. As Vince has mentioned earlier, that uses data actually to power the network effect in health care. Specifically, I think we’re pretty excited about some of the early moves of artificial intelligence to improve the analysis of imaging, for example, with radiography or even pathology images. And you know, it might be fascinating for your audience to know that, you know, these days, it’s not unheard of for artificial intelligence systems to be more accurate at diagnosing, for example, tumors in a breast image than a radiologist would be. Of course, you know, these kinds of things aren’t necessarily replacing physicians anytime soon, but they’re certainly putting more and more strain on physicians to exert their expertize in training these algorithms and facilitating the development of the AI. And likewise, on the receiving side of it, physicians, I think, are more and more likely to be enabled to do more or to do more faster, more accurately, et cetera, when an AI engine is alongside of them.
Jody Ranck: [00:14:07] And actually, some of the research we’ve been doing a little more recently on that non-clinical applications, looking at hospital operations and revenue cycle management and so forth. We’re beginning to see people talk about digital transformation in terms of an AI first strategy. So going beyond a point solution for prior authorizations, for example, and thinking of that end to end revenue cycle management process or in that the hospital operations from supply chains and so forth, where you can build in these feedback loops across different types of data they’re collecting on all of these processes. And it’s just kind of interesting in this recent report we released on AI for OPS is what we call it. It’s really focused on the non-clinical how this is playing out. And you can kind of see sort of the nascent ways people are thinking about network effects in that within the context of digital transformation when they’re putting AI is quasi lead role in that process. It’s kind of interesting to see organizations like Change Health Care, for example, have been talking about the AI first type of approach. As we think about some of the points that just came up and we did our AI for OPS report, for example, to look at the impact of COVID on that space. And one of the areas that’s gotten so much attention due to COVID is the rise of telehealth and virtual care platforms. And so there are another platform opportunity that we need to look at. So do you think COVID created a tipping point for virtual care platforms and telehealth contrast today? Just the EHRs? And will it last? What do you see is the future for these virtual care platforms? Looking ahead a few years,
Vince Kuraitis: [00:16:04] I want to put a slightly different slant on what Randy just said when talking about digital infrastructure. I would characterize it as the architectural plan for digital infrastructure has been laid, but there’s a lot of infrastructure that we still have yet to build over the next decade. And what we’re seeing specifically addressing your question, Jodie, around virtual care is a whole ecosystem being built that essentially circumvents the EMR and health care providers and is being built to provide virtual care outside of the current health care system. And it’s being enabled by a lot of investment capital. It’s companies like, for example, Zeus Cormier, which has raised $500 million. We’ll read docs and the the architecture. You have to give a lot of credit to that for what federal legislation has done and what owns and CMS did in specifying that patients will have access to data that we’re going to have standardized APIs around fire. So you know, what I see is really a parallel universe around virtual care and appoint specifically as an example of what’s going on here to was listening to the JPM presentation that was done by Teladoc CEO Jason Gorevic. And my take on that is Teladoc has a vision of becoming a virtual integrated delivery system across referrals. The whole person care is some of the terminology that they used. And the most alarming, or the thing that got my attention the most was his comment about that they’re preparing to take on population health risk. Now that really ought to get the attention of care providers who who now have a slew of new competitors because of virtual care. And you know, I think Teladoc would not use this terminology of virtual i.d.s because it would explicitly acknowledge that they’re competing with the delivery system. But you know, my characterization is it’s hard to see it any other way.
Jody Ranck: [00:18:27] Randy, do you have any thoughts on? I’m the think platforms virtual reality as well.
Randy Williams: [00:18:33] I think Vince is spot on in terms of, you know, there’s so much more to be digitized and virtual care is going after kind of the beyond four walls of the hospital opportunity there. I would add that I think what you’re seeing and Vince alluded to, this is a battle over kind of who is going to own the primary relationship with the patient, the consumer and ultimately a population. And I think, as Vince mentioned, you’re seeing some pretty aggressive activity there to try to move in that direction from a virtual care telehealth platform perspective.
Jody Ranck: [00:19:08] Ok. And another area for four platforms, you know, we’ve spoken about EHRs and in virtual care and A.I. in all of these another opportunities, collaborative platforms and we’ve seen collaborative platforms such as Trouvait Graphite Health and so on. He has launched last year or two, in fact. And so why don’t we talk a bit about what do we see happening in this space where collaborative platforms and why did they come into existence now? What are the prospects for them in the coming years?
Vince Kuraitis: [00:19:40] I’ll take a first whack. And then Randy, we wrote a blog article specifically about this about a month ago, and we profiled Truvada, EcoHealth and Graphite Health. And what you see is each of these platforms is backed by a number of health systems, ranging from four to to 20 across them. Health care organizations, even the largest i.d.s don’t have the scale of Google and Amazon. And so it really requires them coming together to be able to compete. Part of it is being able to compete with large tech companies that are invading health care. It’s a desire for control, and what we see is in the case of graphite health, really a lack of interoperability among existing vendors that are approaching health systems. So what graphite is trying to do is create this app marketplace that I earlier referenced could have been created by the EHR. And the problem they’re trying to fix is that there are hundreds of thousands of apps and patients. Look at this and they go, Which one do I pick? And doctors find that patients come in with 10 patients, come in with 10 different apps, and they throw up their arms and say, We can’t deal with this. So what graphite is doing is is also recognizing how long it takes. They’re trying to standardize the development of these kinds of applications. I think these platforms are going to have some challenges, but I think it’s absolutely the right way for the delivery systems to be thinking about. It’s one technique of many that I think delivery systems have to compete with some of the new entrants in health care.
Jody Ranck: [00:21:33] Right, Randy, would you like to add anything to that?
Randy Williams: [00:21:36] No, I think he’s done a great job.
Jody Ranck: [00:21:38] So as we go towards wrapping up this podcast, let’s talk about the future of platforms in health care and what are the sort of dominant trends or mega trends driving this platform economy, so to speak in health care? And then maybe towards the end of that, you know, so we look at these trends. If you could each give your thoughts on the Big Tech players, Amazon and Google and so forth. Google and even Apple have had some problems multiple times getting into this space and maybe give your after you provide an overview of some of these megatrends. We can end with what you see happening with the Big Tech players and the ones that excel at platforms, but encountering a bumpy road when it comes to health care.
Randy Williams: [00:22:26] Well, I think some of the megatrends that are affecting platforming outside of health care are the same ones that are affecting it inside of health care to varying degrees. So let me start with consumerization and you know, I think this is a big trend in health care that’s going to continue to accelerate in consumerization. You’re really seeing an increase in demand by consumers of health care products and services for things like access, price transparency, affordability, convenience and even matching preferences. And these things are all best met by platform business strategies. Another one that we’ve talked about earlier is that digitization of health care into structured data sets. And again, this is going to continue to accelerate the use cases for artificial intelligence and likely displace gatekeepers as the information that comes from that artificial intelligence approach begins to replace some of the knowledge expertize that health care providers traditionally have been able to protect. Capturing data directly from consumer devices, for example, or in-home technologies is likely to further displace some of our dependency on providers as data gatekeepers. I’ll also mention data fluidity as something that ultimately is the battleground for platform development, and that is the ability to unlock and make fluid the flow of data across entities and systems as data gets opened up and made accessible.
Randy Williams: [00:24:01] This is going to further accelerate platform strategies and opportunities to disrupt traditional health care business models. So I think incumbents are going to see pressure from all sides. You’ve mentioned one of those, which is Big Tech. We like to think of those as platform native companies, entities that are really built on platform business strategies from the ground up. But we’re also seeing encroachment from investor backed entities that are looking to disrupt traditional business models directly with their platform approaches. And then I think the other approach here is the opportunity for hybrids to emerge places where incumbent health care entities begin to embrace some of the market pressure that they’re seeing from Big Tech or Big Retail, or from investor backed disruptive technology companies, and begin to develop either their own platform business strategies or embrace and partner with. As in the case of Truvada and Graphite Health, for example, a platform approach that allows them to extend beyond their traditional kind of pipeline business models to begin exploring and innovating in the platform business model arena.
Vince Kuraitis: [00:25:18] All that, just briefly, a couple other things. One question on my mind, will we see mega platforms in in the U.S. like we’ve seen in other industries? If you’re looking for an example, look at ping on in China as the closest thing to a mega platform. They’re certainly candidates out there. United Health Care Anthem has a digital first approach. Kaiser 80 percent of their interactions today with patients are through virtual channels. And that, in turn, fuels another trend, which is really mergers and acquisitions towards that mega platform as as companies build and build virtual care platforms. Teladoc acquired Livongo Livongo. There’s certainly another potential candidate for for this, so we’ll see lots of consolidation in among platforms as they continue to grow bigger and bigger over the next decade.
Randy Williams: [00:26:24] And I’d like to add, Jodie, if I could, that I think Vince is on to something here around these mega platforms beginning to potentially emerge and what this platforming business strategy does is it really breaks down lots and lots of barriers, for example, geographic barriers or even, you know, cross country barriers. He mentioned putting on a very large fintech platform in China that’s moving aggressively to roll up and integrate health care approaches, as well as financial technology approaches. But I’ll mention another one that’s coming at this from outside of the U.S., but making great inroads into the U.S. already through mergers and acquisitions. And that’s a platform company called Babylon Health out of the U.K.,
Jody Ranck: [00:27:10] Having had some problems with the conversational AI and accuracy and so forth. Given just, you know, what are some of the issues you see there with the Babylon’s of the world? Have they got they overcome some of those initial criticisms when they, you know, the information provided back to the consumer was a bit off the erroneous some cases?
Randy Williams: [00:27:36] Yeah, I think any platform company that comes at health care is going to encounter some, some challenges that are unique to health care, perhaps not necessarily unique to health care, but certainly in spades within health care. One of them, for sure, is the regulatory environment. Another for sure is that the need for trust. And then I would argue that accuracy and fidelity are also unique to health care because, you know, at the end of the day, we’re talking about, you know, not a simple financial transaction, but potentially a life saving or life giving transaction. So I think you’ve raised a good point that, you know, especially places where we’re still innovating and optimizing the artificial intelligence models and so forth. Like voice recognition or productiveness, those are things that are going to need to be ultimately at a higher level of fidelity in the health care world than they are perhaps in a less mission critical space.
Jody Ranck: [00:28:35] Yeah, I agree. I think trust is becoming a bit of a almost like a social currency in this space as it when it comes to A.I. and we’re going to be doing quite a bit of work in the coming months that will mark just on that that trust equation as it applies to AI in particular, not just platforms, but a more general approach. So I’m glad you raised that issue. Well, that comes to the end of this podcast, and I want to thank Vince and Randy for sharing their insights on this. And we definitely look forward to reading your book when it’s out, and they will visit again down the road as your book gets closer to completion. And we’ll be writing that by accompanying this podcast will have a blog post that will have links to a lot of the topics we discussed in this podcast so that anyone listening can find that information rather easily. So thank you for listening and hear us again soon in our next podcast. Thank you.