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Manav Sevak:
Welcome to the Memora Health Care Delivery podcast. Through conversations with industry leaders and innovators, we uncover ways to simplify how patients and care teams navigate complex care delivery.
Matt Troup:
Hi, everyone! This is Matt from Memora Health, one of the medical directors and co-hosts of the Care Delivery podcast. I’m excited today to be joined by Shahidul Mannan. Shahidul, thank you so much for taking the time to come on the podcast today. Would you take a moment to introduce yourself to the listeners?
Shahidul Mannan:
Sure, Thank you, Matt, for having me. Great to be here. My name is Shahidul Mannan, and I’m the chief data officer at Bon Secours Mercy Health. Just a little bit of intro addition on that, Bon Secours Mercy Health is a hospital system with 65 to 70 hospitals in seven states, mostly in Midwest and Atlantic area and also in Ireland. Altogether we have about 70,000 employees and 16 to 20 million patients. And I’m the chief data officer, so in my role, I pretty much oversee anything and everything data related, from platforms to solutions to AI innovations and productizing and commercializing or building our data partnerships for greater good, more innovation, and revenue generation.
Matt Troup:
Wonderful.
Shahidul Mannan:
For my overall background, I’ve been in this industry or around this for almost 20 years. Most of it is in financial technology for a long time, but the focus has been data analytics and technology, and then I’ve also been in high-tech industries and then in healthcare for the last five, six years.
Matt Troup:
That’s great. I’m excited to dig into a lot of this and especially given your background. But we’d love to know first what inspires the work that you do, especially in recent years transitioning to the healthcare industry. Kind of what was the journey, and how has that been now getting into healthcare, which has a lot of its own challenges and opportunities?
Shahidul Mannan:
Excellent question. So I truly believe that with my, I would say, well-rounded cross-industry experience and exposure to analytics and technology and overall innovation, I believe this is a great time to be in healthcare. And I have been really fascinated coming into healthcare for two reasons. One is I think that healthcare has long been a little bit behind among other industries in terms of innovation with data and overall just building the digital capabilities and digitization, be it going to cloud, be it capturing all the records and digital footprints from our patients to all activities, and then using that for better insights, better products, more efficiency and cost reduction and better outcome for our patients altogether. So that said, coming from some of the other industries, I think healthcare is just scratching the surface, so there’s tons of greenfield opportunities and tons of ways to innovate with data and gain more with digitization. And the second part that I think is unique for healthcare also is healthcare is extremely data-rich. Once we went over the digitization foundational capabilities, and activities thanks to Affordable Care Act, which first led us to adopt EHRs across the system and capture and become more digital, then now we have the opportunity to see more and more data about our patients. And as we dig further, we realize that there are tons of data in unstructured form, semi-structured form, form in images, in CT scans and X-rays, that can have tremendous opportunities for innovation once we start to unleash them and be able to better manage them, which is still unharvested, still kind of under the radar. So imagine the opportunity once we are able to handle and expose and manage these data better for our greater good. And then, finally, we are, unfortunately, in a world where healthcare is likely not in the best state that we would like it to be. Even in the US, you know, we spend trillions of dollars in healthcare, but there are more to do in terms of our patient coverage, our population health, or just overall health risk management for our entire population. And that is where I think digital healthcare and data analytics and now AI innovation can really help minimize or reduce the cost, increase our efficiency and optimization, and build new capabilities, be it with genomic data or be it with patient history, to provide better high-quality care and target for better and more predictable outcome for our patients.
Matt Troup:
I agree. EHRs represent this enormous amount of contextual data that I think has the opportunity to improve clinical outcomes long term. But one of the complaints I often hear is there’s so much data within the EHR; we’re collecting data minute by minute, hour by hour on our patients, but very rarely is this data actionable, right? You get a discharge summary from an outside hospital, and it’s 15 pages long. And how much of that is actually able to be digested and make medical decisions based on it? How are you approaching that as you think about all the data that you’re collecting within your health system? Are there opportunities to make this feel really tangible to the clinical teams?
Shahidul Mannan:
Excellent question, again, I think the biggest challenge we have are kind of twofold. One is that, as I was saying, getting our arms around the data that we have through our EHR and through our day-to-day various operational systems and building the insights that can help with day-to-day activities from clinicians to our field operations, our administration, and to our financials to claims, all of these. So there’s tremendous work that we do and opportunities that are there, just harvesting that structured data and that patients 360 view of things coming from EHRs. And that’s where I believe is our starting point, and we have laid out our platform, laid out our core capabilities around that, and that insight into data and building those capabilities to make more actionable data-driven patient activities, patient care-related activities is actually making a lot of difference in how we deliver our care. That said, as you said, with all the information that are in our nodes, that in our discharge nodes or hospital nodes, nurse or physician nodes, those are tremendously valuable as well, but unfortunately, 80% of this unstructured data is completely unharvested. So our next challenge and the challenges here, we are trying to incorporate that in our overall data world, how we can build it and build that, you know, longitudinal, rich, patient information, including those unstructured data. And then we are also harvesting or eyeing our various genomic data that can be much more innovative in terms of finding the right cure or finding the right treatment. We are also eyeing in more real-time streaming data coming out of wearables or bedside devices that can actually help improve our quality of care real-time so we can take certain action, understanding or predicting a patient’s certain risk or understanding or finding a particular deficit in our care process. So it’s certainly more and more opportunity as we grow, and that’s why it’s so exciting.
Matt Troup:
Do you find that you have any difficulties with getting buy-in from clinical teams or building trust or credibility in the data that you’re starting to surface, or how have you tackled that, or what opportunities for our listeners or suggestions you might make, as more and more health systems are building out these robust data platforms?
Shahidul Mannan:
Yeah, I think the biggest challenge we have is that it’s too much data, a lot of information coming from all ends, and how do we actually manage them, make them palatable and consumable for our end users, and make it more meaningful to our clinicians, and other operatives to make it more actionable. And, you know, there are so many things that comes together when you are looking at data governance or data quality or building the right data dictionary, building the right lineage to make the data highly trustable and authoritative. It’s an entire set of framework and activities, and investments that is needed to make it all happen, to really build that credibility and build that asset that can drive all these innovations that we are talking about. So my approach has been twofold. One is why, and I compare it with changing the engine of the plane while we are driving it and how we go about is, building that foundational capability and core competencies in terms of not only the architecture and technology, but the data content enrichment itself, building those data governance, data quality and dictionary bells and whistles to make it more easy to navigate and use. But also, we are always hungry and looking at high-value use cases that can add value to the practitioners and to our overall system and ministry bottom line, so a combination of those. As we grow our capabilities and platform, I’m also very keen on delivering incrementally high-value use cases so it gets more real. Gone are the days that, you know, you build something for two years, three years, and then you start to apply and show the value. I think now we are in a state, and rightfully so, that we want to rationalize and justify constantly and make sure we are harvesting the right value while we are building the strategic data assets or long-term capabilities.
Matt Troup:
I agree with that, for sure. Shifting a little bit, I guess, and we think about AI and its impacts now on healthcare, and even in my position now at Memora, as we think about how AI impacts care delivery, what are the challenges you’re seeing with starting to evaluate AI technologies? Are you a believer in the promise that AI can deliver in healthcare, and from a just a data standpoint, how are you thinking about mitigating risk?
Shahidul Mannan:
Excellent point. And I think those are all real, and especially because we are in the healthcare provider area where, you know, we have always, the challenge with limited resources like everyone else. And that said, we definitely want to take advantage of the latest and greatest technologies and the AI capabilities and all the good things that AI is promising and also delivering with us in some ways. So we are focused more on how we can, again, find the right use case and the right problem to solve with AI. I think the biggest challenge is how can we allocate our resources best to harvest the optimal outcome from AI. Because we are not a technology company where we can spend millions in R&D and seed something that we can harvest in 3, 5, or 10 years, right? We have to be judicious how we make our choices and do the investments. So that said, we always look for, again, high-value use cases where we can really find some tangible outcome that can make a difference in three key areas that we are always focused on. One, that is the framework for value-based care, which is cost reduction, patient outcome, and quality of care. And then it turns, so we go by harvesting, working with the field level, and with data democratization. There is a lot of data enthusiasm across the organization, a lot of bright minds looking for new opportunities using the lens of data. So we collect them, partnering with our business or our field level or various hospitals, and make a list of all those use cases that we think are viable, and we could explore and harvest the value I was talking about. And we start with, I usually go for low-hanging fruits, start small, show the value. And as we build those competencies using more low-hanging use cases, build the trust, the partnership, the framework, and all, then we go for more complex and more long investment type of use cases and capabilities, and it’s been pretty rewarding so far. In many cases, we have looked at from our career transition-related various use cases to our patient risk stratification and predicting various patient outcomes so we can tune our resources for the best care that we can provide. And it’s a journey, I believe it’s an exciting time, as I was saying, as we also, this morning actually, I was talking to my colleagues about generative AI and …, how best we can harvest those for some of our population health or even document management notes, management type of use cases. And there are various brilliant ideas that seems like people are adopting, and we, and our teams are coming up with that we could even start with. So my advice, and what I try to follow is, don’t go for the hype, keep the value in mind, but at the same time, don’t be shy to try out the new shiny and cutting edge technologies or capabilities. And there are always goodies that you can start with, even if it’s small. Prove the point and then expand on it.
Matt Troup:
Right, when you’re evaluating new vendors, are there specific things you look for right off the bat, or maybe even just like red flags that, you know, this isn’t even worth even a pilot or a proof of concept? How are you thinking through those partnerships?
Shahidul Mannan:
Great question. I think it is a challenge that we all have on the other side, because, at the same time, we always want to find something that has lower risk, and that means, you know, more experienced vendors, more vendors, who has deeper understanding of technology, the expertise and demonstratable expertise or competencies with other clients. That said, that comes with a cost that usually they are more expensive, and B, usually they may not always be the most cutting edge and innovative in some ways, and I’m just talking about the regular average perspective on this. There are always outliers, right? But I definitely appreciate that, and we do that a lot for our majority of our portfolio, I would say. But then I do keep a part of the portfolio for those innovative, you know, even startup companies who has demonstrated that power of thought leadership or the depth of their expertise and knowledge, even if it’s small, even if it’s a small scale, and we can pick up from there and we can actually do partnership to build more customizable products or solutions, that gives us an edge, an advantage, even with a smaller scale investment. So it’s always the challenge of balancing these two. But again, be aware of the hypes and look for something real through that and … mindset to kind of filter and balance among these variables.
Matt Troup:
Yeah, and how does patient privacy play into that as you think about these types of proof of concepts or working with vendors, like what’s really top of mind as you entertain some of these products?
Shahidul Mannan:
Patient privacy and our data custodianship is prime for us. We take it extremely, extremely seriously, not only for regulatory and compliance reasons, but our overall ethical mission and framework that we go by. So that is our first, actually, litmus test of anything and everything we do. And I work very closely, we have a very robust framework working very closely with our chief of privacy, our chief of compliance, head of legal counsel, and chief of security, information security. So we all, combined, always weight out or discuss or try to build the right framework and bells and whistles before we try out any new technology or any new capability or partnership, so that’s number one. And that also meant I’ve been very blessed that we started a little bit earlier than many, and we have built that competency internally and that mentality of embracing newer and innovative products and capabilities with this C-suite partnership who are open-minded to even cutting-edge technologies to see what’s the best combination of things we can do while we are abiding by all the regulatory and our compliance custodianship responsibilities, but able to attempt or able to participate in this innovation journey. And the best way we are able to now handle it, just one last thought on that, is we have actually figured out and adopted various technologies for not only security management or data management better, but anonymization de-identification in an extremely robust and reliable way that is industry, top cutting edge technology and highly adopted and audited in many ways. So when we try those, we definitely go for those trusted and tested technologies to be able to participate in this innovation journey.
Matt Troup:
Yeah, I like that perspective. It’s, keeping patient privacy is the top priority, but also not being afraid of innovation and pushing forward, especially with the current climate of healthcare and where we need to really start to excel. And speaking of, with your background in fintech and other industries, have you been able to bring any lessons learned from those industries into your time in healthcare, or is it, is healthcare just too unique to really find, you know, some analogous challenges and opportunities?
Shahidul Mannan:
No, I have, actually. I think when you are working with data and all the exciting things that happens in the innovation and AI journey, there are a lot of similarities across industries, and the data set or domain is different, obviously, and some of the regulatory and other environments are different, but there’s a lot of similarities when you can apply the learning from fintech into healthcare. And I think healthcare has two advantages, as I mentioned. One is that there are some proven and really tested technologies and use cases in fintech that we could easily adopt with some of these bells and whistles I mentioned about data privacy management. So those are, in my view, are really low-hanging fruit for healthcare to really scale up quickly and be a partner in data journey quickly, which we are doing. And second is, we have an advantage a little bit over fintech in some ways that our data is much more diversified, diverse, and in many ways rich and high volume. And for that, because if you look at all our digital footprints and the channels for data harvesting and collection, it’s just enormous, from EHRs to bedside devices to wearables to lab results to city scans and genomic data, you name it. And eventually, the social media data and others can heavily contribute to our patients’ journey evaluation and longitudinal patient information. So that also gives us an edge because I think eventually, although the outcome is very much measured and driven by the final AI product or data product at the application level, the engine is, I think, better run and more and more powerful, where you can find better, bigger, and high-quality data. Ultimately, it’s the data that makes a difference in many ways. I think healthcare, in general, has high potential and high differentiating, I would say, competitive advantage in some ways, too.
Matt Troup:
Yeah, well, I’m certainly excited that you are now putting your efforts towards making healthcare better and pushing us forward in innovation. I guess to wrap up here, I would love to know if there’s one thing you want listeners to know about being data-driven and in healthcare; what would that be?
Shahidul Mannan:
One very important thing for healthcare, and I’m talking about most of the participants in this industry being new to digitization in some ways, is that build a data-driven culture and mindset. That is the first thing you want to do, and you want to do it through evangelism. You want to do it through demonstration and building the trust and collaboration, and you want to do it by providing better access to your users. And finally, adoption of data and data-driven insights and capabilities across your tangible operational level and all the stakeholders. That’s how you can build the right culture. And once you have the culture, it kind of works on its own. The ecosystem runs towards becoming more data-driven and more innovation-focused with AI.
Matt Troup:
Yeah, that’s so great. Shahidul, thank you so much for spending time with me today. I’ve learned so much. And you know, I think everything you’re talking about in terms of being data-driven is just exceptional. It’s the direction we need to head, and so, thank you for your insights.
Shahidul Mannan:
Thank you, Matt. I really enjoyed the conversation, and great meeting you and your audience. Good luck to us all for innovating in healthcare and solving our healthcare challenges.
Matt Troup:
That’s right. Good luck to us all. Appreciate it. Hope to talk again soon.
Shahidul Mannan:
Thank you.
Manav Sevak:
Thanks for listening to the Memora Health Care Delivery podcast. For more ideas on simplifying complex care for care teams and patients, visit MemoraHealth.com.
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