Next Level Innovation Requires Next Level Data... and Courage

Brian Urban:
Yes, this is the Healthcare Rethink podcast. I'm your host, Brian Urban, and today we have a very interesting guest joining our show, Dr. Emily Lindemer, and she is coming from Morgan Health where she is the VP of Data and Innovation. This is going to be a really exciting episode. Emily, thank you for joining the show. Thank 

Emily Lindemer:
You for having me, Brian. Happy to be here. 

Brian Urban:
This is going to be a lot of fun in particular because we got to know each other a little bit before the episode. I don't always have the chance to do that with a lot of our guests, but let's get to know you before the PhD, Emily. So how did you get into the greater healthcare ecosystem, even maybe going before your startup, a very successful personal startup of yours. Hey Charlie, let's go back more toward the beginning. What was your influences in getting into healthcare data and innovation? 

Emily Lindemer:
Wow. I feel like I've taken a pretty non-linear trajectory in my career. So trying to think of where the right beginning of that thread is. I think when I was a teenager, actually, my grandmother developed dementia and it was probably the first most up close and personal experience that I'd had with somebody becoming frankly irreversibly ill. And really kind of seeing that experience up close and seeing just what the state of the healthcare system was and our understanding really of human health triggered something for me. And what that really was was this interest in the human brain actually. And so I decided to around that time that I really wanted to pursue neuroscience and potentially with a path to med school one day. And so I ended up at McGill University in Montreal because they had a really phenomenal neuroscience program, which when I was going into college was not very common for undergrad. 

Emily Lindemer:
I think it's very common now, but back when that was many years ago, neuroscience was not common for undergrads. And so I chose McGill and while I was there, I went from a deep desire to be in a practicing physician to really wanting to be someone in research who is doing more behind the scenes work and figuring out the why underneath a lot of what was happening in human health. And as a strange kind of intersection in that process, McGill required all neuroscience students to take a computer science course as part of their degree. And frankly, I kind of went kicking and screaming. I said, this doesn't make sense. Why do I need to do this? And much to my surprise, I loved learning how to code. I really became very into it to the point that I changed my degree to computational neuroscience with a minor in computer science, and I left undergrad with this highly computational research oriented attitude towards medicine. Whereas at the beginning I think I went in with this biology and medicine perspective. So definitely changed a lot over those few years. 

Brian Urban:
That is so interesting, especially kind of the nuggets you shared there, looking at your background, and I think looking at a lot of backgrounds of PhD or MDs, you see this linear track, but yours not so much the keen screaming part I would not have predicted. And I do want to talk about your PhD. We talked to a lot of PhDs, DrPH, MDs on the show. Your program that you did at MIT and Harvard is exceptional. It is the combination of two worlds that nowadays, from my perspective and I thought I think a lot of other next generation physicians think this too should be put together. So this was an MIT and Harvard program together, but studying in a lot of the things that you were starting to talk about computation data, you got to be on the floor of hospitals and see how the next generation of physicians were being trained. So let's get into this program. One, I would assume you probably got recruited into this or how did you find out about this type of program? How does this program exist? 

Emily Lindemer:
It's a good question. It's hard to find. So after undergrad I was working, I spent a couple of years working as a research assistant at the Boston va and I was doing neuroimaging there on a really large national project for veterans with PTSD and traumatic brain injury. And so it was kind of like this marriage of computer science and neuroscience via neuroimaging, but right up close with medicine. And there was one of my supervisors in the lab there also kind of co-supervise some students that were in this program called HST, which stands for Health Sciences and Technology. That's through Harvard and MIT. So for a lot of people know how connected the Boston ecosystem is in healthcare, so people have joint labs with multiple institutions. And I was lucky enough to be in the lab of someone who is connected to this program and said, Hey, this is something you should think about. And so I was definitely not recruited into the program. Nobody is recruited in 

Brian Urban:
Sense, right? 

Emily Lindemer:
It's really hard to get into in terms of the interview process, but I don't think I would've actually ever known about it had it not been for this supervisor because I was looking at PhD programs by basically googling like bioengineering and none of them fit this mold of this program. 

Brian Urban:
That's so interesting because well, I think honestly I've done similar things like that relative to public health as being very specific to what I wanted to do. But in a sense, you got recruited to this program and it's interesting, I looked at your pathway in terms of your career. So Wellframe, city block, Morgan Health, it seems like the combination of what you did with your PhD program took you into this really interesting track and took you more and more to the finite world of where you're having a very big impact. I am curious on the medical side of your education, what was it like being shoulder to shoulder with some of these next generation physicians that were in this program, but maybe in a different bubble and then sharing that bubble with you? What was that like? 

Emily Lindemer:
I mean, fascinating. It was so fascinating. I feel so grateful for the experience. Some of my closest friends I think are people that are going to be the leading oncologists of the next 20, 30 years because of who I met and who I got to work with in that program. Some of them have gone on to create amazing startups in areas of medicine that needs so much attention. And so I think I'm so grateful for the network of colleagues that I made. And that was, I think one of the most amazing things about the program, like you said, is that it's not just an engineering, just a biomedical engineering program. The program puts you through what is equivalent basically of a full year of med school with the Harvard MD students. So in classes with them learning some of the core medical classes, pathology, cardiovascular pathology, respiratory, and it ends with you being essentially a first year medical student on the wards in one of the local hospitals working full shifts. 

Emily Lindemer:
It's a three month internship where you really don't do much else during that time. You're solely focused to practicing and learning the practice of medicine. I say that with the full disclaimer that my understanding is just the surface because of the limited amount of time, but I still think that that three months is enough to really change how you think. As an engineer, it's amazing to say this, but I assisted in C-sections. I actually physically pulled babies out. I can't believe I got those experiences, but because I did, I think about these problems so differently. And I think that's really what's invaluable about the program and the way that we're trained. 

Brian Urban:
Wow. I got some goosebumps with that because we're both parents, the experience of having children and obviously our experience is different sides of it, the power of emotions and everything that goes through it. And you were seeing it from the delivery end. This I didn't know in particular about your background. So having that experience that's coded in your brain, and I'm sure that now through the rest of that program you were in, you took those experiences and you probably saw things from such more of a matrix perspective, everything around that woman's experience having a life coming into this world. So I'm curious, as you were going through the rest of that program, you started down, I think this was, I'm going in sequential order here, I think then you eventually started your own startup. We want to get into Hey Charlie. But in between that little timeframe, did you start to feel the desire to have more of a play with women in stem because that's a part of your background relative to this program, but was that a light bulb after some of those medical experiences that you're like, Hey, I need to have more stronger partnerships and more women need to be elevated in these types of programs. 

Brian Urban:
Is that something that came out of that? 

Emily Lindemer:
Absolutely. It's funny, I mean, even thinking back to my time at McGill, I did a minor in computer science and it was probably 5% female in my degree. It was really, really stark, and I thought that maybe it would be better at MIT and MIT is pretty gender balanced in a lot of departments, but when you get to the graduate level computer science courses, the people who are really getting PhDs in computer science and electrical engineering, which was the other side of my degree. So the other side of the medical part, it was still actually kind of similar gender balance. I mean, there were some of those really high level courses where it was maybe 20% women sometimes. And it's funny how it affects you. I think it affects you in ways that I kind of didn't expect. I mean, it's difficult to find a group of people to be doing your P setss with, and that is a huge part of your grade in these courses. 

Emily Lindemer:
So just finding peers to collaborate with, there's a gender barrier there. And so it was part of the stuff that I saw on the wards for sure, women's experience in medicine, but I think it was women's experience in computer science. That was one of the more initial switches for me. And I did two things in grad school, I think directly because of that. One was I became an instructor for the National Girls Who Code Association, which is awesome. So I would teach girls from sixth to 10th grade every Monday night at the local library how to code. It was awesome. And I also became the co-chair of graduate women at MIT. So that was more of a university organization to support the professional development of graduate women. Both were such rewarding and awesome experiences. 

Brian Urban:
I didn't know about the more youth side of your contributions in that space, but it has to start there. I don't think you can just go to a graduate level and say, Hey, we need more women. We balance this out. You have to start in earlier years. So that totally makes sense. I'm not sure if that was your strategy. I would assume it is. And you connected both worlds quite well. So I wanted to get that perspective because I think it's different in so many different M-P-H-M-B-A programs, MD MPH programs that are combining a lot of these different worlds and interdisciplinaries together. And I think that the balance needs to be there. And it hasn't traditionally, it seems like it's becoming like that a little bit more. So thank you for the insights of this program. It was just so fascinating. Now I got to go a little bit more into the future here. Hey, Charlie came about, this is a beautiful startup, if I can define it like that. Very personal to you. And it had a lot of great success very fast. So would love to understand how that birthed and how that started to grow in such a rapid fashion. 

Emily Lindemer:
Yeah, I think some of the origins of it were from my time on the wards in training as well. I had a lot of patients who came in with some kind of physical ailment and you start peeling back the onion and you realize that the root cause is something social. People couldn't afford their insulin. And so they were trying to manage their diet without taking medication for their diabetes or people who were getting really bad skin infections because they were too depressed to change their compression socks. And it's like these people end up in the hospital and your job as a clinician is to treat the reason they're in the hospital and send them home. And all of those underlying root cause things often go unaddressed and they come back and everyone in medicine knows this. And it's not a failure of doctors, it's just this sense that as a system, there are so much under the surface outside of the four walls of healthcare as people say that is so difficult for people to address. 

Emily Lindemer:
And so that was part of, Hey Charlie, but hey Charlie specifically. So it was a digital health company that I developed with a couple of co-founders, and it was specifically to treat the social underlying causes of addiction relapse for people with opioid addiction. And it was specifically born out of a lot of observations with someone really close to me who's struggling with addiction for a decade. And this observation that whenever they were able to maintain sobriety, the thing that would trigger them to relapse was often based on the people that they were starting to hang out with again. So this person would stay sober for sometimes months, sometimes be able to get a job, be financially stable, and then as soon as they started getting phone calls from people from their past, you could predict their relapse to AT. And it was kind of this observation that this is happening, but it's a medical problem, but the medical system can't fix this root cause was sort of what we were trying to do. And so we developed a platform that essentially ran in the background of people's phones. It was an app, but you didn't really use it and it would just give you little nudges anytime someone risky for you called you or texted you that said, Hey, are you sure you want to pick up the phone right now? Are you sure you want to talk to this person? And it would give you a pre-created text message that you could send. So you didn't even have to put in the cognitive work to say no. 

Emily Lindemer:
I mean, it was an amazing experience building it. We got it into the hands of real patients. We sold it to a couple of organizations. But it is a very difficult thing to make a business model in our healthcare system. 

Brian Urban:
I love the story about this, and we talked personally about this before the recording here. I find it just so mission-focused, heartfelt, meaningful, and needed now than ever. And we've talked to a lot of different healthcare tech startups, cas AI being one of them, cloud Medex, a lot of them that focus on niche or particular challenges within someone's care journey or life journey overall. And the funny thing, and I know you believe this, Emily, looking at CFOs today, it's starting to roll over into a new generation of CFOs, CEOs, CMOs in healthcare health plans. And they understand this. A lot of them speak to this, but a lot of them sometimes I feel don't realize they need to be a part of this journey, otherwise the responsibilities that come along with their leadership is falling to the ground. So I'm curious, what would you say to the next generation of c-suite executives or even below that feed into those leaders where mental health and these very, very specific types of tech solutions should be? What would a message be to them from you saying how this needs to be important, how this needs to be incorporated into the person's journey, a patient member, whatever? 

Emily Lindemer:
Yeah, it's a really good question. I will say that specifically if we're talking about mental health and substance use disorder and these types of areas of healthcare that we want to see innovation, one of the things that I think I see I wish I would see happening more is people developing a real understanding of what the experience of those patients is. And I'll give you an example of this. Hey, Charlie came out of an MIT hackathon. So it was like this one weekend problem pitch ideation process where you get 48 hours to basically try to come up with a solution to a complex problem. And my team, and I said in that 48 hours, who are we to say what the solution is for someone suffering with substance use disorder? None of us have that. And we actually were so bold as to pick five different subreddits for people struggling with addiction, put out a survey to all of them that was like, hi, we are from MIT, we want to solve this problem, but we're not you, are we? 

Emily Lindemer:
Right? And these communities gave us back so much candid, helpful, grateful advice about what their actual experience was, where we were right, and where we weren't quite right about how they were struggling and what kind of support they needed. And it was really amazing actually, to hear these people be like, we can't believe people from MIT are coming to us. And I was like, that's exactly what should be happening. And I know there's, every company has a user experience division. I know companies know that you need to be doing your user research, but there's some kind of organic level of understanding that I think often doesn't happen in the early ideation phases 

Brian Urban:
That I think is a very great statement that I think a lot of our listeners will be able to understand. I hope they can take action upon that. Hey, Charlie, it was an amazing story. I loved your work there. I would understand that part of that led you to go into more data and innovation and healthcare ecosystem now with Morgan Health. So I'm curious now, Emily, what are some of the big impacts you're hoping to make in the work that you're doing today? 

Emily Lindemer:
Yeah, so I have definitely exactly taken this kind of journey from where I started with brains and neuroimaging into data in the broader healthcare system. And it's really exciting work. I'm really excited to be at this point in my career. What I have found happen since between grad school and now Morgan Health, is that I have started to play roles at the systems level when it comes to data in healthcare. So rather than applying data to imaging or applying data to a specific disease area, my career has grown to viewing data across the whole healthcare ecosystem, all of the different players who use data, who need data, and trying to figure out where things fit together and where there are gaps. And so at Morgan Health, what we specifically do is we are really aimed at trying to make employer sponsored healthcare better. So for the half of the American population who gets their health insurance from their employer, we are really focused on how can we make healthcare more affordable, equitable, and accessible to people? And I play the role of doing a lot of the data work behind the scenes to answer some of those questions and drive some of those decisions. And so given that stat, if it's half of America, I would hope that the impact can be somewhere even in a fraction of that, 

Brian Urban:
And it has to start somewhere too. So the affordable and equitable side of your work, of your work, very daunting, that task, those words. I was just at a conference this past week, NCQA, innovation Summit, great place. They're trying a lot. I think they're really pushing a lot of initiatives at the right pace in terms of really how can we not flip the switch necessarily, but how can we get more fast adoptions of things that are very obvious? We've talked a lot, you and I, about the social health challenges that aren't seen outside of the physician's walls in an E-H-R-E-M-R and other parts of the clinical workflow. My biggest challenge in a lot of the health equity conversations this conference and other ones is what's the data you're looking at? Are you continuing to look at clinical data, claims data? That's only a small piece of the pie. 

Brian Urban:
That's where you are seeing the spend and utilization. You try and route it back to the services, but what's causing the spend? What's causing the utilization of service X, Y, z? And my head in a lot of ways, just goes back to socioeconomic data. What's your influences at the household individual level where you live, your employment, a variety of other things, food, transportation, all the things that you and I have talked about before. Are you starting to see the hunger for this across the ecosystem? Maybe not just in your particular lane of work, but are you starting to see a desire for, hey, what are the other alternative data sets that we could start to consume and play around with? 

Emily Lindemer:
A hundred percent, yes. I think that the appetite for looking at data outside of claims has grown astronomically in throughout my career since the beginning where I think claims was kind of just like, that's the standard. That's what we have, that's what we use. And people would kind of say like, oh, there's these Z codes in claims that correspond. And I'm like, no doctor is using those. I've seen Z codes entered five times in claims, and that's not the signal we want to be using. And so there's a couple of very exciting things that I've been seeing happening to try to get at this. One of which I think you're very familiar with. And you mentioned socioeconomic data is really looking at spend data if you can get it, there are companies out there that are aggregating data from tons of different sources, like everything from DMV records to credit bureau data and putting it together to try to drive the development of social risk scores, sometimes social risk scores as they tie specifically to healthcare. 

Emily Lindemer:
So not just likelihood of having transportation, but likelihood of being able to be transported to a hospital. People are trying to be more targeted in driving those insights, which I think is great. The other thing that I'm really excited about, and again, I'll tie this back to my experience on the wards is when you are a doctor, you write something that is called, sometimes they call it a SOAP note, but it is basically like a personal history with the current problem of the patient that you are seeing right now. And there is a section in there standard that's like social issues. And of course, depending on the amount of time the clinician has and who the clinician is, maybe they don't write that out as fully as the next, but that's the place in the doctor note where sometimes they write down, this person is living with five cats. 

Emily Lindemer:
And that's how you figure out that that's why they have this weird bacterial infection, but there's no ICD code for that, right? That doesn't get to claims or it's where you find out that they're in and out of housing. And so what I've seen that's been super exciting is a lot of work towards large language models and NLP in general towards extracting that social information from the handwritten or typed in doctor's notes and bringing that as data that can be used more readily by researchers, by organizations to supplement claims data. Because even though it is still being captured within the four walls of healthcare, I wouldn't call it in the four walls of healthcare data. 

Brian Urban:
Yeah, I going to say outside. Yeah. 

Emily Lindemer:
Yeah. So I think those are two areas where I'm really excited and hoping we get more and more progress to bringing social data into kind of the standard taxonomy. 

Brian Urban:
I love the example you gave. I'm not very familiar with that level in terms of the soap noes, but very much so in terms of the NLP and a lot of other program language that's trying to extract that and put it into something more visible or more actionable. It is funny because we aren't there yet in terms of a regulatory measure or a HEDIS connected measure that says, Hey, did you capture X, Y, Z and actually address X, Y, Z? And then how did it get into the claims flow? That's the barrier you just described, is these data does not get into the claim flow at all today. But I'm curious, do you have an encouraging comment for those larger healthcare systems or even smaller ones that have an appetite for this type of alternative data to get ahead of the curve before regulation might come into play in 25, 26? 

Brian Urban:
Because it looks like that's where it's going. I mean, you're capturing, there's a lot of requirements now in California that require capturing race, ethnicity, language data, but there's also the social needs screening that NCQA has put forth into CMS and they're saying, you got to do screening, but there's nothing really after that step. So I guess what would be your message to organizations that are hungry for this, that want to do it, but maybe haven't put it into a standard practice or haven't really flushed out or shared anything that they're doing with the rest of the ecosystem? 

Emily Lindemer:
So I haven't thought about the answer to this question till right now. So this is a little off the cuff, but it is a really interesting question with this thought of large language models, NLP, these are things that are rapidly becoming more available to everybody. There are these really easy APIs that now so many entities are able to just plug some information into or ask a question and get something back. So the technology is becoming more and more accessible to everybody. What you need to be able to do, I think, to leverage these technologies, as is always the case, is have your underlying foundational data be complete. And so for hospital systems that want to put in more practices into place to ready themselves to be able to use these technologies, I would say adding more standardization around the way their clinicians are collecting. Even that handwritten data in notes, train your clinicians, tell them that it's critical. 

Emily Lindemer:
There's a requirement that when they are doing their just even annual evaluations in healthcare or when they're doing their patient intakes in the hospital, that a certain amount of content is collected for patients about their social history. Because if that exists, we now have the technology to extract it. Whereas before you could make the case, like we write it down, gets lost in a note that no one ever looks at, but now people are going to be able to start leveraging those notes. So if the data's there, we'll be able to pull it out, which I think is hopefully that's promising. 

Brian Urban:
I like how you answered that. I mean, I don't mean to even ask all these crazy visionary questions to you, but it's great to have your insights applied to where we are, where we should be. And I think, Emily, you nailed it so well. Well, before we get there, foundationally, we need to be more strong. We need to be more well coordinated and standardized. So that's a definite part of carrying this forward and to being able to see everything that's happening outside of physician's office or connected to it that is driving the spend, that's driving utilization, et cetera. So I'm just so excited that we've had this time to get really deep in a lot of the work that you've done, a lot of the stuff that you're doing right now. So Emily, I want to take a look into the future. A couple of years down the road, maybe three or more, what do you think Morgan greatest contribution will be to the healthcare ecosystem? 

Emily Lindemer:
Oh, wow. I have so many hopes for what that could be. So let me pick, I'm going to pick one. It's not necessarily the one, but I think it's really relevant to what we're talking about. I really hope that Morgan Health can help surface how we need to close health equity gaps today, specifically in the employer sponsored insurance space. Because for Medicare and Medicaid, there are things that are going into place about health equity. People are really tackling those problems at the state and the government levels for employer-sponsored health insurance. I would like, and I think Morgan Health would like to be at the forefront of figuring out how to do that for the other half of Americans who are getting their health insurance through their employer. So really setting up ways that we can understand what the health disparities are and how we can close them. That would be, I think, one of the biggest contributions we could make. 

Brian Urban:
I love that you said the word help several times. A lot of people I've been hearing the last especially month in this heavy conference season, we're coming to a close here, is solving or eliminating. Oh my goodness gracious. So that right there is maybe reaching beyond a lot of human capacity, tech capacity that we're aware of now, but helping and making a very meaningful contribution toward a very specific area. I love that you said that that is a very real thing that can be achieved. So it gets me excited. I love what you're doing, Emily. Your background is so fascinating. I wish you all the best and all the work that you're going to continue to be a part of going forward. So thank you so much again for joining our little show here today, Emily. 

Emily Lindemer:
Thank you, Brian. This was so fun, such a great conversation. 

Brian Urban:
Loved it. And for more exciting insights and excerpts, please visit us@fint.com.