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Becker’s Healthcare Podcast
Healthcare Upside / Down: Navigating AI in Healthcare with Asif Shah Mohammed and David Schoolcraft
00:31:44
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- [00:00]
A
Welcome to Healthcare Upside Down, a podcast by Becker's healthcare and ECG management consultants, in which we'll explore the upsides and downsides of healthcare and the industry's most current trends. I'm Molly Gamble, and today I'm thrilled to be joined by two guests. Asif Shah Mohammed, partner and head of digital innovation, ecg, and Dave Schoolcraft, partner with Ogden Murphy Wallace. Asif. Dave, welcome to the podcast. Thank you so much for joining me.
- [00:26]
B
Thanks, Molly.
- [00:26]
C
Thank you, Molly.
- [00:28]
A
Well, welcome. Welcome. Why don't we take a moment at the top here to learn a bit more about each of you and your perspective on our conversation. Today we'll be unpacking best practices for health system executive teams and buyers to better navigate this crowded, hypey, distracting AI market we're in. So before we dive into that, let's learn from each of you more about your background and your work. Dave, can I start with you first?
- [00:53]
B
Oh, sure. Happy to jump in and thanks for having us. Just quickly, I think the easiest way to describe my background is I'm a digital health lawyer. I've kind of been practicing at that intersection of healthcare and technology for longer than. Where does the time go for, I don't know, 25 plus years? So I've seen several waves of technology starting in the late 90s, early 2000s, up until today. And I think as Asif and I talk quite a bit, I think this is a really exciting time. The other thing I would say, just briefly, I like to think that I can speak kind of multiple languages in this neighborhood at this intersection of healthcare and technology, in that my practice is span from representing those that are builders of tech, but also those who are deploying the technology. As I like to say, I can speak both hoodie, if you will, on the builder side and suit on the deployment side.
- [01:58]
A
I love that. Both hoodie and suit. That's great. Well, great perspective, Dave. Asif, let's turn to you. What would you want to add about your perspective on this big topic and then also a bit more about your background and your work, of course.
- [02:10]
C
Appreciate you having us here today, Molly. I'm a partner at ECG Management Consultants. We are a national healthcare consulting firm where I lead our digital innovation practice. I've been at the firm about 18 years, and throughout my career here, I have focused on helping our clients effectively navigate the operational and strategic implications and the implementable reality of health care technologies. So much of my work in the last few years has been facilitating the development of actionable recommendations on how do you prioritize digital investments to compete, to differentiate and develop innovative business models that can help to elevate the patient experience and to drive operational and clinical excellence. Of course, in the last couple of years, faced with rising technology costs, increasing documentation burden, leading to clinician dissatisfaction, and the need to enhance consumer engagement, EHR modernization has increasingly become top of mind for most healthcare system boards and the C suite. And this is where the promise of AI is starting to come in. Dave and I talk a lot about this. The power to transform the the EHR from this passive data repository to a high performance digital asset that can help organizations to ultimately unlock the full value of their data, enhance those workflows, improve outcomes and quality optimized margins. So our work is increasingly focusing on how we can help our clients sift through the Alphabet soup, if you will, of AI jargon. So I'm very excited to have this conversation with you and Dave about how to use this rapidly evolving technology enabler to solve for some of the most prevalent challenges that I think we've been dealing with our entire careers. Right. Workforce shortages, physician burnout, improving patient access, reducing the cost of care.
- [04:35]
A
Asif, thank you so much. I think you, you lay the groundwork beautifully for sometimes I think with AI there's this recency bias where we think everything is new. And then I think as both of your careers with 25 years, Dave for you and then Asif, 18 years at ECG help us appreciate is sometimes what old is new again. And I want to make sure we're starting with a crisp understanding of where we stand today. You know, I if you hint at EHR modernization becoming really top of mind for most boards in C suite, we're a little past the midpoint of 2025. In some ways it feels like we're at this interesting, quiet, but turning point in the industry's AI storyline. And asif, I just wanted to get some more thoughts and observations from the ground if we can. What are you hearing from health system partners at ECG right now about the challenges they face when it comes to decisions about AI investments, deployments, moving from pilot to purchase, and implementation? I mean, there's a lot demanding their attention right now. What are some big headlines that you can share with us?
- [05:42]
C
Great question and I love the way you framed it as if old is new again. AI has been around almost my entire career. I was an electrical engineering undergrad way back in the day and we talked about AI as AI is evolving. What stands out is this focus on human interactions rather than replacing it. What we're seeing in the market today is that health systems are just now working on trying to unlock the value of AI in their respective organizations. As a result, while the adoption of AI is accelerating, it's still relatively low with many initiatives that are driven by largely by bigger health systems or academic medical centers. And many of these are still pilot projects. Much of that tangible value proposition and the demonstrated return investment for health systems that are early adopters has come from the ability to automate and streamline administrative and clinical processes. Many organizations are attempting to take a AI first approach. Organizations in doing that are looking at the native AI powered features that are built into their legacy EHRs. These EHRs are still rules based. They have to be manually configured. They are very narrow in scope or they're poorly integrated across your ambulatory, acute and post acute settings. All these tools that are built in, they may deliver incremental value, but they're not necessarily driving transformation just yet. So for example, take patient access or consumer access. EHRs are not integrated into their digital front doors. The patient portals lack conversational interfaces. Scheduling is often disconnected from clinical triage or capacity management. There's opportunity to guide patients intelligently to shape access, improve the consumer experience with clinical documentation. This is probably the area where AI has the most tangible impact. And this is what everybody's talking about today with ambient listening. But it's still in its infancy stage. Most documentation still remains unstructured, which limits analytics, the ability to follow up coordination, the ability to summarize records across clinical disciplines, and the ability to get reimbursement accuracy. So our clients are challenged to differentiate between the array of market options that are available to them today. With operational optimization. The current tools are very, very reactive. Most AI investment is still focused on clinical burnout, not workforce efficiency with staffing adjustments in real time or anticipating the bottlenecks for the enterprise throughput. For example, revenue cycle tools are still rules based. There is opportunity to identify the right investments that will result in decreased denials, improve cash flow or reduce financial coding or reimbursement related risks. And finally, health systems are sitting on massive amounts of data within the EHR and this could be used as a strategic asset. While doing this, we want to ensure that all of that sensitive patient data being used to generate predictions in the AI modeling or learning models, they're being handled with the highest degree of privacy and security considerations. This is where many of the regulatory aspects are coming into play and where Dave's expertise comes in as well. Given all this, we believe that no one vendor can solve for all of these problems and relying solely on the EHR vendors landscape could be a strategic risk for our health system clients. So identifying and investing in the right AI use cases with vetted technology solutions that align with an organization's overarching strategic and operational goals. This offers a way to leap ahead of the competition, an opportunity to turn many of the stagnant infrastructure into a key differentiator for clients.
- [10:20]
A
Asif, I hear you. It sounds like from your state of the union you're really seeing clients. It's tough to decipher, like you said, the array of options available to them in the market in addition to all the internal bottlenecks and redesign that they'll need to do to, to test those solutions. And David, I mean you bring the legal and regulatory perspective to this conversation. You have so much expertise in licensing, data governance, privacy security. I think Asif set us up here really nicely when he mentioned the sensitive patient data. But that all adds another dimension to AI decision making. All that fine print that I imagine can be a lot of what keeps leaders up at night. What are you seeing health system leaders really wrestle with the most right now in those areas?
- [11:07]
B
Yeah, I think. And also that was a great kind of overview of all the decision making that's going on. I think in terms of what I'm seeing, number one is just the speed with which leaders are having to try and make decisions. I mean it's super exciting. If you think about it, what we've done over the last 20 plus years is lay down the infrastructure in health care to be able. I think about the label was the North Star, was that we could create a learning health system. As we moved from paper records to electronic, what we got is a lot of information, we have a lot of data, but. But are we able to get the insights right? And so now we have. And as Asif said, you know, AI and healthcare is not new. What's new is this, is this new form of AI, not the rules based deterministic AI, but the generative AI. And it's amazing to think how quickly that things are changing. So it's super exciting. I think we're going to see, for example, you know, I think about how long it took to go from the concept of hey, it would be really great if we digitized health information. We could lower, we could have higher quality, clear, lower risks of bad outcomes, lower risk of errors and things like that. Well, it took the better part of 30 years to deploy that tech. AI is not going to take 30 years to deploy this technology in our healthcare system. In fact, if you think about this tech, it unlike enterprise software, which was very top down, no one was going to deploy an EHR unless the entire system decided to. And Asif and I worked on lots of those contracts right over time. Whereas this technology is different. It can be deployed very much on a bottom up basis, which is exciting but also daunting from a risk and compliance or regulatory standpoint. And so that's where I'm seeing a lot of excitement, but I'm also seeing a lot of anxiety around how do we get our head around this? And that's where I think, as I think about some of the work that ECG has done to try and identify those companies in the market that are solving certain problems, vetting those companies, putting them together in an organization that can help a hospital system deal with that speed, be able to deploy things quickly without having to worry about individually vetting every single company.
- [14:00]
C
Right.
- [14:01]
B
And then the other thing I would say is just I'm all about, you know, it's kind of like, you know, there's a, there's an inspirational component to this. There needs to be an educational component to this which is part of what we're doing here. And there needs to be a collaborative component, the educational support that's so important. Where I sit and I talk a lot with general counsels and compliance officers and CFOs. It's like you need to have people at your, you need to either do the work yourself or have people at your side that can help you navigate the, the, the, the distinct nature of this technology. Look, this is information technology, but this is not old school if then statement algorithmic software. This is something different and super powerful. But we got to get our head around what it means that this software is not deterministic in its nature. It's more probabilistic. So to your question, Molly, how do I see this showing up in terms and conditions? That's a lot of the work that we're doing as lawyers in the space is helping organizations think through those things. And it all starts with understanding the nature of the technology, what it's really, really good at and what it's not good at. You know, there's a professor at, at the Wharton School named Ethan Mollick. He's written a book called Cointelligent. He and he talks about the jagged edge of progression, knowing what this tech is really, really good at and what is not ready for prime time. And again, I think that's why I love, helps me to Collaborate with somebody like Osip on this stuff because I trust that he and his team have done the work on evaluating what, what the tech is good at. And I can stay in my lane and making sure that, you know, the contracts, you know, line up with, with, with what, you know, the, the customers are looking for. So I know that's a lot, but it's a really exciting time and, and I think, you know, with the right navigators, organizations can really lean into this tech.
- [16:03]
A
Yeah, no, David is a lot, but I think that's why we're here. Right? We're going to be talking about this new collective effort from ecg. But before I do, I think just to underscore what you shared, what you just described there with the vetting and the technical understanding and education, I mean, that could easily be a second, third full time job. It sounds like, it just sounds like it takes a lot of energy, a lot of time, a lot of resources. Which Asif, I think, brings us to Cypher Collective. This is a new curated marketplace from ECG of AI enabled health technology partners looking to bring more efficiency, scalability and clarity to this crowded vendor landscape. Asif, can you talk a little bit about the origins of this idea and this collective and how you really see this marketplace functioning?
- [16:50]
C
Yeah, I'm really excited to share the Cypher Collective, which we launched about two weeks ago. Someday I hope Dave, you and I get a chance to sit over a fireside chat and really talk about the origin story. And Dave was integral to the, to the origin story here. I think this idea germinated about a year or so ago with all of the different AI vendors that are out there. And we started getting calls from many of our clients where the CIO said, hey, my board is reaching out to me and they say, what do I do about AI? Where do I even begin? What should I be thinking about? Which initiatives should I pursue? And CIO is saying, I'm just getting inundated with every single vendor in the market calling me and trying to pitch me an AI product. So we said, okay, as we discussed a little earlier, there is no one size fits all to solve for all of the challenges that healthcare organizations are facing. It will require developing a set of strategic partnerships to really deliver a true transformation. So we designed the Cypher Collective as a answer to this problem that clients are facing today in making their decisions around AI. To be a. The cyber collective is effectively a curated partnership or ecosystem, if you will, that's powered by ecg. Our vision is to help health systems navigate The AI hype distill the vendor market landscape and the Cypher Collective provides a single platform for clients that need assistance with their governance models, regulatory and legal guidance with Dave Zell implementation frameworks to maximize the value of their AI initiatives. This is supported by vetted best in class technology enabled solutions that together create a force multiplier that will help to unlock the AI opportunity. Or at least that's our vision. The AI ecosystem helps providers and payer clients navigate the hype. The fragmentation of all the AI landscape brings together a rationalized set of vetted solutions. We help our clients assess where they are on the AI maturity spectrum and then develop a governance model to prioritize where they should invest. Each of the strategic partners that are in the Cypher Collective have discrete capabilities that address a wide range of key use cases that align with ECG's core strategic advisory and performance transformation expertise. And with our collective capabilities, we hope to provide a differentiated go to market offering that will result in increased revenue, improved margins or enhance the experience for patients, providers and staff. So if you'll indulge me for a minute, let me walk you through a scenario for how the Cypher Collective can support the end to end patient journey. Imagine AI agents that can guide the patient using digital triage, recommend the right care setting, then alert the provider to intervene at the right time and populate the EHR with key information before the patient even arrives. With the capabilities that we have in the collective, we have the ability for AI to listen across multiple specialties. So summarize data in real time, flag incidental findings and support the end to end front end and clinical staff that allows them to operate at the top of their license and minimize low value at work. Our solution partners can forecast demand. They can align staffing, predict supply inventory shortages. We proactively support revenue cycle management to accelerate collections and all of the structured and unstructured data. We're able to synthesize that in real time to drive population health contracting investment strategy and service line redesign. And we do all this building upon the legacy EHR investments. So our value proposition to the market and our clients is that we will simplify the contracting process with a single master services agreement so clients don't have to negotiate multiple technology contracts with multiple vendors. The single marketplace of solutions provides an easier way for healthcare organizations to find vetted solutions and we will also implement all of these AI driven automations that address these top challenges in an optimal manner.
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A
Asif, a few things really stood out to me there. One was the precision of what you just described. So getting back that maturity score and then the matchmaking that occurs at the collective to being brought to the right partners and tools with those discrete capabilities you had mentioned. And thank you for the walkthrough. I think that's really helpful. As someone who's visual myself, Dave, I'm going to turn to you here because I think embedded in Asif's comments is the concept of trust. And this is such a recurring theme with like you mentioned, vendors, contracts, the tech itself. We are seeing just a lot of hype continue to unfold in this market and I'm curious about some of the gut checks you would recommend in addition to these trusted sources like Cypher Collective that can certainly help. What other best practices would you advise health systems to consider or follow to really kind of distinguish marketing claims from, from real commitments?
- [23:02]
B
Yeah, I think, you know, I'm, I'm reminded of, I can't remember who said it recently I listened to and just been reading so much but the line was that the limiting factor in being able to deploy AI for good in healthcare, that the limiting factor is not the tech itself. The limiting factor is trust. It's almost like the infrastructure of trust that we need to build up around the tech. And some of that comes from contracts. And I think to your question, Molly, I think people have to go in and ask the right questions of their vendors and basically expect that their vendor is presenting to them a contract that is just like the tech needs to be customized for healthcare, like AI as a general purpose technology. Fantastic. But it needs to be customized for healthcare. Right. And similarly the contract terms and conditions need to be customized for the nature of this technology. And so that's one thing for sure. I think the other part about this is, is doing is going through that kind of vetting process where I think it's really important to you know, take a breath, pause and you know, ask ask the hard questions of, of the vendors that you're going to rely on, whether it's the administrative side of healthcare or the clinical side. And, and I think that you, you know, I think Asif and team at ECG kind of listening to their clients especially like, I mean you talk about massive health systems that may have all manner of staff but, but, but a medium sized health system, let alone smaller health systems, they may not have the staff to be able to get through that vetting process to be able to, to get to that level of trust that they need to get to. And, and I think that's, that's part of And I can let Asif speak to it. But my sense is that that was part, part of the driver to say, hey, you know, listening to our clients, we need to help them be able to make good decisions here and, and help, you know, them find the right companies to collaborate with, etc. So I think back to your, your core question, Molly. I think it, it's, it's asking the right questions going into, with your eyes open, expend expecting your vendors to, to have a set of contract terms and conditions that kind of match the nature of, of the tech. You know, we could also talk a little bit about evolving standards, organizations and the regulatory environment which I think will catch up. But the state that we're in right now, we're not going to really be able to wait for the rules to come. We're always with cutting edge technology out ahead of the rules. And so it really is up to collaboratives like the Cypher Collective to kind of come together and work with their, their clients and customers to try and again get the most out of this amazing technology.
- [26:09]
A
No, thank you, Dave. I think that makes a lot of sense and I think what you had described, you know, ask the right questions, expect it to be customized and then also I think Asif, hopefully Dave's remark there about the size of the staff and resources different organizations have to this vetting process can really vary. So having a collective available could be such a step up and create a bit more equitable of a process for so many different systems as we wind down here. I was just thinking as you both were speaking about how far we've come compared to even a year ago and Dave, you had said how fast things are moving. If we had to look forward as we conclude and you had to make one expectation or something you would like to see in how health systems are evaluating and implementing AI, how it would change or shift by a year from now. What would you put forward forward as something that you're crossing your fingers on? Asif, can I turn to you first?
- [27:05]
C
Sure. Actually I have two things. First, I hope that health systems will consider the Cypher Collective over the next one year. Having said that, we hope that looking ahead to a year from now, healthcare organizations will really start to see the increased economies of scale from many of the common use cases that AI and AI will deliver measurable impact that can be tracked. We know that quantifying ROI is not always straightforward. There are indirect benefits. Isolating the exact contribution of a technology enabler to financial gains. It can be tricky and low adoption rates can also limit success. This is why any evaluation of an AI strategy will need to take that balanced approach, combining financial metrics with qualitative impact assessments for sustainable adoption. I also hope that despite the rapid evolution of AI, we don't lose track of the fact that healthcare at its core is still human. I came across an article recently by Blake Madden reminding us that at the end of the day, healthcare is still driven by relationships. No amount of AI can replace this very foundational aspect of our industry or AI software alone cannot drive meaningful change. Much like any other technology solution. It requires the interplay of people, process and technologies to drive transformation.
- [28:52]
A
Thank you Asif. Dave, same question for you. Something that you would like to see shift or progress in how health systems are evaluating and implementing AI from a year, a year from now?
- [29:02]
B
Yeah, I'm going to just kind of riff on what Asif just said there. I mean, you know, all I've wanted to do with the last 25 years of my career is help know, answer two questions. One, how can, can technology, information technology help our healthcare system? And number two, how can I help? Those are the two things I want to work on. My hope for this technology and, and I've seen a lot of tech deployed and, and, and not necessarily enhance that human aspect of care. My hope and I'm going to use my, my 87 year old mom as the focal point and my hope is that this technology can allow my mom to have a big better. I mean she's got a great doc, but that doc is seeing a lot of patients every day and that doc maybe doesn't have as much time to sit there and hold my mom's hand and talk about what she needs to do and that it's going to be okay. And if this tech, from the administrative side to in the exam room to after to eliminating the burden on the doc so the doc can give my mom more human to human assurance so that my mom walks out of there. My mom shouldn't know what the tech is behind the scenes. Right? But the human aspect of care and that patient to physician interaction just again reacting to what Asa said and thinking about at its best what this technology can do. It's not the robo doc, it's the tech letting the human doc be at their best. That would be my hope that we could see that start happening in the near term.
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C
I love that.
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A
I think that's such a paradox of what we're talking about is that for all the tech and all the fine print and the technical requirements in education that demands. At the end of the day, it's just trying to increase the humanity of the health system in so many ways. So I think, Dave, your remarks, and Asif, too, yours, really just underscore that beautifully. We'll close out here. I want to thank each of you for being my guest. Asif, is there somewhere listeners can go if they like to learn more about the Cypher Collective?
- [31:13]
C
It's on the www.ecgmc.com our website, and there's a link to the Cipher Collective page.
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A
Perfect. Listeners, you heard it from Asif if you're interested in learning more about the collective. Asif Shah Mohammad, Dave Schoolcraft, thank each of you for being my guest today in this really insightful conversation. And my thanks to ECG Management for their sponsorship of today's episode. Thank you very much.