How Standards Drive Innovation

[00:00:00] Will Crawford: Hi, everyone! Welcome to Hard Problems, Smart Solutions, the Newfire Podcast. I’m Will Crawford, Head of Advisory Services and CTO at Newfire Global Partners, and I’ll be your host for this episode. Today I’m talking with Dr. Paulo Pinho. Over his career, Paulo has straddled the line between care delivery, payer technology, and entrepreneurship

[00:00:27] Will Crawford: including stints as Chief Medical Officer of Discern Health, and his VP and Medical Director of Innovation for Diameter Health and Availity. He’s also a practicing physician. Today, we’re talking about the evolution of healthcare standards and the importance of clinical informatics for healthcare innovation.

[00:00:43] Will Crawford: We’ll explore how advances in standards have enabled new kinds of applications, including ones that leverage AI and some of the challenges that come with those changes. We’re also going to talk about the transition from clinical medicine to the corporate world. And how as a non-clinician, you can work more effectively with your clinical partners.
Dr. Pinho, welcome to the podcast.

[00:01:03] Dr. Paulo Pinho: Thanks, Will. I appreciate being here and, uh, looking forward to, to digging in for sure.

[00:01:09] Will Crawford: So before we dive into, uh, specific topics, could you just tell us a little bit about your journey in healthcare?

[00:01:16] Dr. Paulo Pinho: Yeah, so a, a little bit of an unorthodox journey. I, um, you know, started out in, um, in clinical practice right outta medical school.

[00:01:23] Dr. Paulo Pinho: I’m a primary care, uh, physician, board-certified in internal medicine and pediatrics. Um, and worked in both disciplines, had my own practice that I was able to build up and, you know, started to experience many of the challenges that exist in healthcare delivery, um, from a, a data standpoint, from a quality of care standpoint, the defining what quality care was for individuals.

[00:01:45] Dr. Paulo Pinho: Ended up selling my practice to a hospital system and, uh, it was early on in the consolidation of hospital practices and eventually I, um, uh, actually made the move to more executive health roles, uh, initially with, uh, Prudential, where a lot of my work focused on things like thoughtful benefits, benefits design, um, really creating sort of an engaged and empowered workforce,

[00:02:07] Dr. Paulo Pinho: you know, using, uh, benefits design as the foundation for that and, you know, really using it to drive employee engagement, et cetera, and then moved out into the healthcare data standards world, predictive analytics world and AI world. So it took me a while to kind of realize the scale and the opportunities that exist, uh, when you use technology to enable the way healthcare is delivered.

[00:02:28] Dr. Paulo Pinho: And I think that now more than ever, it’s, you know, becoming a need. I, I think you have to mitigate some of that supply demand mismatch with thoughtful, uh, technology solutions. And so I’m excited to be part of this, you know, new wave of tech-enabled healthcare.

[00:02:44] Will Crawford: So for people listening who you know don’t come from that clinical informatics background, uh, could you just talk a little bit about why data standardization for these applications is so complicated?

[00:02:56] Dr. Paulo Pinho: Yeah, so I think dating back to the meaningful use days, it’s, uh, it’s really been a significant challenge. Data in healthcare by definition, is multi-source and multi-format. It’s been increase, there’s an increasing amount of medical data that’s created for each individual with nearly a thousand percent increase in, in data capture on individuals over the course of the last 10, 10 years.

[00:03:17] Dr. Paulo Pinho: Uh, and we also know that medicine is becoming increasingly complex to the point that the, this full body of medical knowledge is, uh, increasing at rapid paces. I mean, we know that, uh, medical knowledge doubling, you know, as of 2020, was at 73 days, and so it’s only shorter at this stage of the game. We know that there has been sort of a challenge in healthcare in terms of evolving off of, uh, legacy systems.

[00:03:42] Dr. Paulo Pinho: Uh, we know that despite the fact that meaningful use was, uh, intended to drive data interoperability, it really created a bunch of different formats of data could be captured within providers’ offices. There were, uh, different electronic health record platforms. Each had their different way of sort of collecting data.

[00:04:00] Dr. Paulo Pinho: Uh, each had their different key pieces of information and sort of, and, and its storage in different areas of the electronic health record chart. And then, you know, you could have two separate implementations of the same electronic health record in two different hospitals that were across the street from one another.

[00:04:15] Dr. Paulo Pinho: And the way they captured data was very, very different. So, um, despite the fact that meaningful use intended to sort of wrangle some of this in, it really created a bunch of different languages. And then on top of that, a bunch of different dialects as well. Um, and we know that the language of clinical data capture was very different when you’re capturing data for clinical intent versus when you’re capturing data for billing purposes.

[00:04:36] Dr. Paulo Pinho: Uh, we know that providers, some of the data that we, we capture when we see patients tends to be, you know, very structured codified data that we pulled out from pull-down menus. Um, but in other times you really can’t tell a full narrative story, um, unless you actually type in pros. And so some of that’s made data standardization really, uh, complex.

[00:04:55] Dr. Paulo Pinho: I think on top of that, we’re starting to see data capture in a bunch of different formats that we never thought would be, uh, data, you know, methods of data capture. Uh, we know that data is captured, you know, outside of electronic health records that’s really meaningful to healthcare delivery, for example.

[00:05:10] Dr. Paulo Pinho: There’s an increasing amount of wearables that that, that are out there, and we’re seeing people diagnosed with atrial fibrillation for the first time, you know, from their Apple watch, or with sleep wake disturbances from a wearable ring. We know that there’s social data aspect, uh, that that, that, you know, can’t necessarily be capturing the same way

[00:05:27] Dr. Paulo Pinho: from electronic health records. And so ultimately, you know, the types of data that really have become meaningful to today’s healthcare delivery in a, in a personalized fashion, um, have become too difficult to consolidate. There is a challenge in sort of the volume, velocity, variety of clinical data and nonclinical data that drive healthcare outcomes.

[00:05:49] Dr. Paulo Pinho: Um, and, and that’s I think probably where the biggest challenges lie. And there is, there are increasing challenges when it comes to, uh, data privacy, data security, um, et cetera. And so, you know, while there’s a lot of opportunity with the, the sheer amounts of data that we’re collecting in healthcare, I think the challenges and the complexities of the different ways that data is, is, is collected,

[00:06:10] Dr. Paulo Pinho: the different languages and dialects have really made it so that interoperability, despite its most pure intent, has have, has really been elusive for the healthcare industry at the stage of the game.

[00:06:22] Will Crawford: So the mechanics are there, but the sort of semantic agreement on what gets exchanged over those pipes, there’s still a lot of work to do. When you talk about medical knowledge doubling every 73 days, just tell us a little bit more about what knowledge that is.

[00:06:40] Dr. Paulo Pinho: We see this right now. I mean, I, I remember practicing medicine while I was in residency. I would say that, when I first started in residency, HIV, for example, was an inpatient disease.

[00:06:54] Dr. Paulo Pinho: We managed, I would say, that probably 70, 80% of the patients that I was taking care of on the wards, um, even in the pediatric wards were HIV positive individuals that had an opportunistic infection. By the time I graduated residency, HIV had shifted to largely in outpatient disease. Um, you know, focused on giving people the right highly-active anti-retroviral therapy, um, to prevent some of these opportunistic illnesses.

[00:07:19] Dr. Paulo Pinho: And so, um, we didn’t have inpatient disease. It was a complete shift. I mean, I would say that if I had 20% or less of my patients having, you know, HIV, um, that was probably a, a large representation by the time presidency was over. We’re seeing this with cancer care. You know, when you look at how cancer has has been treated up until now, it’s really been this sort of race against time.

[00:07:41] Dr. Paulo Pinho: You know, we’re providing the body with a poison in the hopes that killing the cells that are responsible for this tumor happens at a rate of speed that’s quicker than killing the cells that you know are keeping a human being alive. Um, and you know, now with more targeted therapies that are, you know, molecular-based and focused on cell surface receptors and really personalized to the type of cancer that someone has,

[00:08:06] Dr. Paulo Pinho: you know, we’re really able to sort of augment not only the quantity of life for individuals, um, who have these cancers, but also the quality of life because that side effect burden just isn’t there. And so, you know, I think every era is defined by a clinical illness or a set of clinical illnesses. I would say that my residency training was defined by sort of that rapid evolution in, in, in HIV treatment.

[00:08:30] Dr. Paulo Pinho: And I think future generations is, are gonna be the cancer personalization and the cardiovascular disease personalization that exists. And these things are happening very rapidly. I mean, when we look at cancer care, you know, I think that we’re gonna have a generation of clinicians 10, 15, 20 years from now, they’re gonna look back and say, wait, let me get this straight.

[00:08:48] Dr. Paulo Pinho: This is how you used to treat cancer? You used to give people poison and hope that it wouldn’t kill them and kill the, kill the tumor. This is the kind of, you know, information that’s doubling and doing so very rapidly. It’s not limited to cancer or HIV. We see it in cardiovascular disease and, you know, we see the ability to personalize medicine, to do it in minimally invasive ways.

[00:09:09] Dr. Paulo Pinho: It’s changing the access opportunities and the quality of care that we deliver, um, in ways that we never thought would be possible 10, 15, 20 years ago.

[00:09:20] Will Crawford: So I, I think that’s a great example. I mean I, I have some people in my life who have benefited from some of those targeted cancer therapies, and it’s, it’s really been remarkable and it’s been very grateful for that because it would’ve been a very different story, even a, even a decade ago.

[00:09:36] Will Crawford: But bringing those two themes together, I, there’s a lot more information around the patient and then there’s a lot more knowledge to apply that information to. So how are providers keeping their head above water?

[00:09:49] Dr. Paulo Pinho: Yeah, I think, um, medical education has definitely needs to, to pivot and I think it already has started pivoting, obviously providing sort of an evidence-based strategy for literature review.

[00:10:03] Dr. Paulo Pinho: For how, and we saw this during the COVID Pandemic, there were tons of articles that were released and some of them were sort of in holding patterns, and we needed that data as clinicians to be able to make informed decisions about our patients and how do we do that in a way that’s thoughtful?

[00:10:20] Dr. Paulo Pinho: How do we do it to make sure that what we are releasing to clinicians who are using these to kind of make decisions about their patients is done so in an informed and an appropriate way and that it’s not quackery. And so I think that part of our medical education system now has evolved to really be very critical of medical literature and sort of some of the technology adoption that’s happened.

[00:10:42] Dr. Paulo Pinho: Um, and I think that was really ushered in by the COVID Pandemic. Um, it’s been ushered in by the need to personalize, you know, healthcare for individuals. Physicians, nurses, nurse practitioners, physician assistants, they all recognize at the stage of the game that, you know, having that information accessible in the quickest possible way is important.

[00:11:02] Dr. Paulo Pinho: So you see people using smartphones on a regular basis, or tablets on a regular basis. You see electronic health records embedded with solutions that allow providers to look for critical studies that may help sort of guide care. You see clinical decision support systems that are being embedded in electronic health record workflows that are guiding clinicians to make the right decision and really sort of absolving them of some of the administrative hurdles of the daily practice of medicine.

[00:11:28] Dr. Paulo Pinho: And I think you see the advent of solutions that are coming up that you know, obviously need to be done. So with a lot of responsible use of comfort level with artificial intelligence, comfort level with things like large language models, comfort level with things like ambient listening and how that factors into the way data is captured from a patient at the point of care.

[00:11:50] Dr. Paulo Pinho: And so I think there’s whereas medicine training tended to be very apprenticeship based in my, in my days of training, I think there’s a lot more flexibility built into the way residents are trained in today’s day and age to not only sort of retain some of that apprenticeship training, but also give people the flexibility to go out and sort of experiment with new technologies of data capture, new technology, of, of grabbing insights about diseases and treatments.

[00:12:17] Dr. Paulo Pinho: And so I’m, I’m excited at the evolution that we’ve seen in medical education for that reason.

[00:12:23] Will Crawford: So I wanna go back to that concept of comfort level, especially with AI. Medicine is a very historically rigorous, evidence-based culture. AI models, you can’t always tell what’s going on inside. And yet there’s so much value in things like document summation.

[00:12:41] Will Crawford: I remember having people talking to me 10, 15 years ago about the need to pull in a medical student to do a chart biopsy on a new patient who came in and go reading through every previous node, and I, I, I sort of became very enamored with that for his chart biopsy. And I was saying it too often for a while, AI can do the chart biopsy.

[00:13:00] Dr. Paulo Pinho: Mm-hmm.

[00:13:00] Will Crawford: It could probably do the chart biopsy as well as many medical students as the provider who’s making a decision about care. How do you get comfortable?

[00:13:11] Dr. Paulo Pinho: Yeah, so I wanna approach it from a couple of different angles. There’s a story that I, I routinely tell that, and there’s actually a really good article by Reinhardt, uh, that was written in 2020, and it was really about the stethoscope and how the stethoscope was ushered in and became something that

[00:13:26] Dr. Paulo Pinho: physicians had a comfort level with, and so it was invented in the early 18 hundreds. And at this point, uh, as we think about its adoption within the United States, American physicians really had to attend lectures and, and clinics in Paris to really learn from some of the fathers of the stethoscope and relaying it.

[00:13:44] Dr. Paulo Pinho: René Laënnec was actually the person who invented it. And the challenge was, is that it was limited to very elite physicians who happened to work in academically affiliated medical centers. And so it wasn’t every doc who was seeing every patient that was able to see it. Adoption was slow, and I think there was a lot of reasons why adoption was challenged.

[00:14:02] Dr. Paulo Pinho: There was a lack of formal education. You know, there wasn’t really a lot of bedside training that was available with the stethoscope. There was a complexity that existed in the way interpretation happened. And how to sort of, what do we do with this atory information that’s coming? There was a hesitancy to create this barrier between the patient and a and a clinician by putting an instrument in between them.

[00:14:23] Dr. Paulo Pinho: And then there wasn’t really a lot of opportunities for continuing medical education that physicians could join into after they’ve left medical school. And so a lot of the learning tended to stop, you know, when they left medical school and that was, so, it was probably a little less than a full century

[00:14:40] Dr. Paulo Pinho: before, adoption was so commonplace and it would be hard, you’d be hard pressed to find a physician that graduates from medical school that doesn’t own a stethoscope, hasn’t used one. And granted, there’s technology that’s evolved to replace a lot of the things that we did with stethoscopes and do so better.

[00:14:57] Dr. Paulo Pinho: But it’s such a central concept to how we trained as physicians. And I think we’re going through some of the same challenges with artificial intelligence right now. There’s a lot of information that’s coming at us, a lot of noise that exists, a lot of bias, a lot of reluctance to adopt because of the fact that we’re fearful that it creates a, a wedge between us and patients.

[00:15:19] Dr. Paulo Pinho: I think there’s a lot of value to provide that, that AI provides in doing some of the things that tend to be very root. Quite honestly, physicians don’t have the time to deal with. If you go to an emergency department and you ask the average doc, how many pages do they sift through of a person’s past medical history before they abandon and ship, and then go in and ask the patients,

[00:15:39] Dr. Paulo Pinho: I think it’s, the number is somewhere around like seven pages. Right? It just, there’s so much information that’s gathered in that medical chart. Some, a lot of which is repetitious, a lot of which may not even be correct in terms of the way it’s captured. AI is a way of kind of sifting through that and making it so that it’s streamlined.

[00:15:56] Dr. Paulo Pinho: There’s so much nuance that isn’t captured. Like I, I used to think about the way I used to write my clinical notes. I would go in and have an interview with a patient and have a, it was a conversation and then translating that conversation into something that would be necessary to, to document code and bill, I’d lost so much of the nuance that was so critical for differentiating some of the gray zones in people’s diseases, and that information was lost forever.

[00:16:22] Dr. Paulo Pinho: And so things like ambient listening, while they may be something of uncomfort in the room at the point that it’s being captured. Oftentimes, they provide much more granularity and much more nuance that’s really important to ultimately making the right decision for patients, making the right diagnosis, and prescribing the right treatment.

[00:16:40] Dr. Paulo Pinho: I, I do think that there is going to be an adoption issue and a comfort level that people are gonna have to get through, but there’s no way that it’s sustainable at this stage of the game. Where a clinician sees a patient, you know, and for every hour that they spend seeing a patient, they document for another half hour after that.

[00:17:00] Dr. Paulo Pinho: Right. That’s just not sustainable when we’re, it’s sort of seeing the dwindling numbers of providers and increased numbers of patients that are increasingly becoming complex. In terms of how we adopt it’s really the thoughtful learnings from technologies like the stethoscope that we think about how we as a medical discipline start to adopt technology in a way that’s that’s comfortable.

[00:17:22] Will Crawford: Thinking a a little bit more about some of the, you know, the natural language processing element you were just talking about clinical documentation, do a little experiment, like if you get a letter back from a, on a patient you sent out for a consult, and the first line is, thank you for this very interesting consult. What do you read between the lines there?

[00:17:42] Dr. Paulo Pinho: I’ve had that statement represent a whole bunch of different things. One thing is, I don’t know why you sent this to us, because you probably could have figured it out on your own. You’re a primary care doc and you practiced internal medicine and you went to residency with me.

[00:17:56] Dr. Paulo Pinho: I’m calling it interesting, but it’s a little tongue in cheek and this is probably something you could have figured out on your own. I’ve been in academic medical centers where there’s some sincerity to that. There’s there there’s some, it’s a convoluted case that involved a lot of information gathering.

[00:18:10] Dr. Paulo Pinho: Perhaps I, as the primary care doc, have gathered some of that information and synthesized it in a way that I was able to send it to a specialist and the specialist pieced it all together and, because of their area of expertise came to an easier diagnosis. I’ve seen both of that, right? Both of those circumstances where on one hand it’s, hey, I just realized that the reason why you sent me this patient is because I’m an ENT doc, and this person had a nose.

[00:18:33] Dr. Paulo Pinho: And then other times it’s, hey, this is a really complex case, you synthesized this very nicely and I got a lot of information. But I think like I think when you look at AI from a medical decisioning standpoint, some of that information gets glossed over, right? What’s really of essence is, hey, this is a 53-year-old male with past medical history, significant for A, B, C.

[00:18:55] Dr. Paulo Pinho: They’re on these medications, these are their allergies, these are social vices. They presented to you with a complaint of X and this is what you saw on the physical exam. I substantiated by finding this. I did a couple of extra tests and in the end I’ve come to the conclusion that this is what the diagnostic, the diagnosis is, right?

[00:19:13] Dr. Paulo Pinho: It really, I think, a good consult letter not only starts with those sort of entry statements and sort of exit statements, but they really have a lot of information about the Socratic method that medicine has practiced in, right? How we gather information from a subjective objective, make an assessment, make a plan for what this patient has.

[00:19:31] Dr. Paulo Pinho: And that’s where I think AI has become really good at pulling out of these consult notes to really help make informed clinical decisions.

[00:19:37] Will Crawford: And that was the theme that I was hoping that we could dig in on a little bit because there is so much context and things that are written and things that are not written in these notes.

[00:19:48] Will Crawford: And you know, I remember working with people years ago where simply pulling out someone’s smoking status from a, and this was before that was a required field as part of meaningful use, was incredibly different. Difficult ’cause you only had the free text node and non-smoker quit last year is very different than non-smoker.

[00:20:11] Will Crawford: Which is very different than 12-pack-a-day smoker quit 10 years ago. And pulling that into a format where you could make a, actually make a decision is this patient eligible for a trial? Are they in a real-world evidence cohort? That’s interesting is very challenging and I, I think while we have a lot more coded data now, we have a lot more complexity that we need to work through as well.

[00:20:35] Dr. Paulo Pinho: You know, I think you look at SNOMED for example, it’s become really expansive and you could really capture a lot of the pros documentation in, in, in structured format. It’s still not perfect and it’s not a hundred percent. And there’s, I think the other thing is that as we think about why physicians document,

[00:20:54] Dr. Paulo Pinho: yes, some of it is to create a historical medical record, but that really drives care. But there’s a whole lot of other reasons why they document to protect themselves medical legally. They document to establish patient satisfaction. They document for the purposes of building and coding. And so sometimes it’s really difficult to sift through that.

[00:21:13] Dr. Paulo Pinho: And I think you can look at the situation where in a consult letter, there’s an intro sentence and you can decide, all right, what’s ultimately the meaning of that. But I think if someone, for example, if you wanna allude to the fact that someone’s, you believe that someone’s an alcoholic without allowing it to be a risk factor for you from a, from a medical legal standpoint, because you didn’t address it.

[00:21:35] Dr. Paulo Pinho: While you also don’t want the patient to see their record where you’re insinuating that they’re an alcoholic, so that you’ll lose trust with a patient who you’re trying to essentially get to the bottom of things. It’s a really dicey way about how to appropriately document in a clinical loop, right, and still capture the nuance.

[00:21:51] Dr. Paulo Pinho: Still capture, still protect yourself from a medical legal standpoint and still establish and continue to establish that trust with the patient because they ultimately get to see what’s written in there and dissecting that, from an, from a an NLP standpoint, that becomes a bit of a challenge, right?

[00:22:07] Dr. Paulo Pinho: Because you don’t know what the, what were the motives for documentation in this particular note?

[00:22:12] Will Crawford: For companies that are developing, whether it’s ambient documentation systems or other AI assistive technologies, where should they be focused if in terms of creating trust with physicians?

[00:22:26] Dr. Paulo Pinho: Yeah. I mean, I, I think as I’ve been educated in, in informatics and what I think, I think a lot of the, a lot of the times physicians

[00:22:35] Dr. Paulo Pinho: are afraid that the, these solutions are coming to, to are being adopted, not necessarily to drive the improvement of the patient experience or to diminish provider abrasion, rather to make it so that workflows that are more administrative in healthcare that lead to better billing and coding and reimbursement, things like that are really the motivating factors.

[00:22:55] Dr. Paulo Pinho: And while I think we always have to focus on return on investment when it comes to a lot of these solutions, some of that investment is in some of that return comes in the form of a life saved or a medication error averted, physicians went to medical school and clinicians went to their professional school.

[00:23:13] Dr. Paulo Pinho: Because they really wanna make a difference in, in people’s lives. And I think we have to resonate with them as we have these conversations with solutions that are meaningful and we have to see whether or not it truly helps it. It helps diminish provider abrasion by implementing some of these solutions.

[00:23:27] Dr. Paulo Pinho: So we wanna make sure that we’re thoughtful about how, what are we have clinicians understand what the motives for implementation are, that they’re truly about helping improve the physician-patient interaction and they’re helping improve the way care is delivery, and they’re helping to reduce some of the challenges that we have as physicians from a rote documentation or some of the administrative billing issues, et cetera. That’s really what I think physicians want.

[00:23:54] Will Crawford: So a few minutes ago, you mentioned SNOMED, and that may not be a term that all the people listening to the podcast are familiar with. So for people who are joining us to learn a little more about the shape of this healthcare standards and data world, can you just give us a two or three-minute tour through the modern coding system?

[00:24:15] Dr. Paulo Pinho: Yeah, so I think a lot of times, you know, as if we’re thinking about the laypeople, there’s probably two codes that they, two types of codes that they see in their medical billing. For example, and that’s usually the ICD-10, which is the International Classification of Diseases in the CPT, which is a, a list of medical procedures that are done, or, uh, the types and intensities of visits that are captured at at, at the point of care.

[00:24:39] Dr. Paulo Pinho: Those are largely transacted to be able to drive thoughtful billing. But electronic health records have become so much more complex in terms of the types of data that sort of, you know, go into them. And, you know, there’s a, a set of terminology called LOINC that’s responsible for how we capture things like blood pressure and how we capture parts of a complete blood count or a comprehensive metabolic panel or a blood culture.

[00:25:04] Dr. Paulo Pinho: There’s parts of medications that actually have a set of terminologies that are associated with how they’re captured. There’s a coding standard that exists for vaccinations, and so a lot of our vaccine registries are set up with that coding standard. And SNOMED is really a, a sort of a catchall set of terminology that really captures not only disease states and their procedures, but also qualifying statements that tend to have adjective and adverb qualities associated with them so that we can get more nuanced.

[00:25:34] Dr. Paulo Pinho: Understand that ICD-10 only classifies things in more broad brushes. I think you can get more specific information about diseases if you start bringing in these other coding standards and really creating sort of an amalgam of these coding standards to help tell a story. And that’s, I think the best way to represent it is that each of these coding standards really is, represents a different part of speech, let’s just say in a sentence so that the full compendium of the medical information that’s captured in that chart has been codified in a way that can be transacted by machines.

[00:26:10] Will Crawford: Well, and we want our audience to be able to sleep tonight so we are not gonna talk about NDC codes and how that works with electronic prescribing.

[00:26:17] Dr. Paulo Pinho: No, no, we’re not.

[00:26:19] Will Crawford: So, pulling all this stuff together, are there categories of applications that you think are just more feasible now, thanks to all this progress, both in standards adoption and in AI? Like what are you excited about?

[00:26:31] Dr. Paulo Pinho: Absolutely. I think, you know, there’s been really an evolution of a lot of different things, and I think just even through my, my career, you know, I can come up with sort of four quick success stories as different phases in, in, in my informatics career that have been really impactful.

[00:26:47] Dr. Paulo Pinho: You know, I think COVID had a lot to do with how standard adoption and electronic data capture, we became more thoughtful about how to do it. And so I had the opportunity in one of my former roles to work for a company that, um, happened to work in a state at the public health level. One of the challenges that existed from an interoperability standpoint is that there were over a hundred different ways of capturing

[00:27:10] Dr. Paulo Pinho: a simple concept like the COVID-19 PCR test and 40 different ways of representing that the patient had a result that was negative. And so if you look at a hundred different ways of capturing the test and 40 different ways of capturing its negative value, there’s 6,000 different permutations that could exist of how that data’s captured.

[00:27:30] Dr. Paulo Pinho: And so you could see where if you create data standardization, it really has a huge ROI impact on public health initiatives. And again, this was only in one state. Imagine what this is across, you know, this is 40 different labs. Imagine what this is across 400 different labs in 10 states. Right? So this, this is a, a real problem that I think technology was aimed at solving and did a great job.

[00:27:53] Dr. Paulo Pinho: I worked with a group of students addressing how to take medication instructions and parse and parse them using not only medication normalization or, or data normalization but then deploying novel solutions like NLP and Gen AI. To really get better F1 scores for some of these solutions, and, you know, the amount of medication instructions that could be parsed once normalization is added to to, to these NLP Gen AI solutions, uh, makes it so that the capture of the information is almost near perfect.

[00:28:25] Dr. Paulo Pinho: So that’s, it’s speaks to the fact that we can really reduce medical errors, which are substantial impact in, into why people stay in hospitals longer, and a significant cause of morbidity and mortality in amongst patients. And then in sort of my most recent role, it’s really identifying individuals and pulling together some of this multi-source and multi-format data, really pulling in a combination of social patient reported outcomes data, pulling in a lot of the medical data from electronic health records.

[00:28:56] Dr. Paulo Pinho: A lot of the billing data and sometimes the incongruence between what’s captured in a chart and what’s what’s billed is actually very insightful. That sort of absence of congruence is actually very helpful in how you build machine learning models. And so we looked at individuals primarily older age

[00:29:12] Dr. Paulo Pinho: with clear modifiable risk factors like things like polypharmacy or the way their homes were set up that were at risk for falls and actually started targeting thoughtful interventions to prevent those falls. And this is really showing that having a combination of data standardization as the foundation for more advanced analytics, predictive modeling and AI

[00:29:34] Dr. Paulo Pinho: is really important to how we make the job of treating patients and doing so in a way that’s contextually appropriate and thoughtful and diminishing in the provider’s burden is really very valuable. So I think those are really four good examples of how automation clinical decision support, and sort of advanced analytics can be used to help drive healthcare improvement.

[00:29:59] Will Crawford: So actually going back to SNOMED. Just listening to this conversation as we’ve been having it, there’s always been an adoption barrier there. It’s obviously a lot of work. It’s a lot more work to enter structured information, and you’ve gotta create an incredible user experience to be able to do that versus being able to write a narrative note. With these newer AI tools and summation have we been solving the wrong problem in terms of designing code systems?

[00:30:32] Dr. Paulo Pinho: Early on, I think the purpose of coding systems was really to automate the way hospitals worked, automate the communication between different areas of the hospital, drive billing. I even think, by the way, I think that’s a very insightful, insightful question.

[00:30:48] Dr. Paulo Pinho: I don’t think it’s even about coding systems. I even think that it’s about the reason why the electronic health record evolved the way it did. It wasn’t. I, I don’t think it was created with a thought in mind that this is the best way to capture data, to create a chart, a living chart for a patient. It was really about how do we create something that lends itself to billing and coding, right?

[00:31:11] Dr. Paulo Pinho: And not necessarily how we create something that tells this person’s full medical story. And so I think the way coding standards did evolve, or at least the way they were utilized, was not necessarily for the primary intent of patient care delivery. I think we’ve done a good job of starting to pivot and really being more thoughtful about how we use these tools to identify opportunities and gaps in care.

[00:31:35] Dr. Paulo Pinho: But I think we’ve been reactive in the, in the way we’ve gone about it, because again, they weren’t set up in a way to drive true chronicling of medical care. They were invented for other purposes, billing, coding, medical, legal, et cetera. And I do think that the technological evolution that we’re seeing now probably is more thoughtful.

[00:31:54] Dr. Paulo Pinho: I think the role of the physician and the clinician informaticist has made it so that we’re being more protective of our turf. We’re not a technology, we’re not a technology person first. We’re a clinician first, right? And we’re building thoughtful technology solutions that help augment the way we can deliver better care for patients.

[00:32:13] Will Crawford: So in a way, we’re, we’re really almost going back to the beginning. People like Octo Barnett and Larry Weed, who were right at the beginning of this electronic record keeping revolution back in the sixties and seventies and had a very clinical, very patient-oriented historian approach to designing these tools.

[00:32:33] Will Crawford: And then the process automation juggernaut took over from that.

[00:32:39] Dr. Paulo Pinho: I think we, we deviated a little bit from that purity of intent early on, and I think that by having clinicians involved in the process now, where I think we’re getting back to it for sure.

[00:32:52] Will Crawford: Continuing on on this theme of clinical adoption, have you seen any organizations that you’ve felt have done a, a really good job and of thinking about the ROI on some of these clinical informatics programs and interviewing the work of their CMIOs into their strategic plans?

[00:33:10] Dr. Paulo Pinho: Um, I think that there’s a lot of very forward thinking. I think there are forward-thinking hospitals that have done really good work around how are we incorporating some of these solutions in a way that’s not just about checking a box and really bringing in the CMIO decision-making, um, into the whole, into the whole process?

[00:33:30] Dr. Paulo Pinho: I think that there are a couple of very thoughtful states that really accelerated the sort of modernization strategies during the COVID pandemic and did so in a way that was thoughtful. I think you’re starting to see a lot of tech-enabled organizations that kind of have come out that are more maybe concierge based or even concierge light.

[00:33:50] Dr. Paulo Pinho: They don’t demand sort of a lot of, a lot of membership dues for patients, but ultimately really deliver hugely tech-enabled solutions. I think that there’s, I, you know, look, I, one of the, one of the indictments that I have of meaningful use is that I think that there wasn’t necessarily the right carrot and there wasn’t necessarily the right stick.

[00:34:09] Dr. Paulo Pinho: Right? It became a really big challenge to get providers to engage because of the fact that it was such a laborious process to get people on board, and then the penalties for non-engagement were actually piddly, especially if you didn’t necessarily have a big Medicare or Medicaid population in your patient portfolio.

[00:34:26] Dr. Paulo Pinho: And so I think that people adopted and there was a lot of checking boxes to say that they adopted. A lot of the initial meaningful use requirements were self-report, and I think when you have that kind of self-report and you don’t have the right incentives to get people to do it or disincentives to prevent people from not doing it, I don’t think that there’s thoughtful adoption.

[00:34:48] Dr. Paulo Pinho: One of the challenges that’s existed is, is that while the capacity exists to allow people to do that the education doesn’t necessarily exist, and I think there are thoughtful hospital systems, thoughtful payers, thoughtful providers that are really making patient education and patient navigation about how to use those solutions

[00:35:07] Dr. Paulo Pinho: a central part, you need to get, I mean, I think the two biggest adopters that need to drive this are your medical staff and your clinical staff and hospitals, and then you gotta get patients on board with understanding about how to do to do this. It’s such a complex care delivery model that unless they’re fully bought in, you could have patient right of access.

[00:35:26] Dr. Paulo Pinho: No one’s accessing it. And so I think, I think that’s really what’s required to have success. It’s really the buy-in of both the clinician staff as well as the patients, regardless of whether it’s a payer provider, hospital system, a concierge practice, a tech-enabled practice, et cetera. Those are the things that are absolutely required.

[00:35:45] Will Crawford: I’m reminded of a conversation from 15, 20 years ago with the uh, CIO of a hospital system that had one of the first patient portals and he told me two things that people use it for refills and appointments, and it’s paid for out of the marketing budget, not out of the clinical budget, not out of the core IT budget.

[00:36:05] Will Crawford: And really they saw it as a tool for retaining their patient population. What are some of the levers that, like that convenience of being able to make an appointment or send a message to your clinician, will help drive patient adoption of these new care models?

[00:36:22] Dr. Paulo Pinho: So I, I think a lot of it is really access. You know, you look at things like mental health, there are some states, and we’re not talking about states that are necessarily significantly poor states, and we’re talking about affluent states that still have challenges with people being able to access crisis care from a mental health standpoint. There, there’s such an issue that in one of my previous roles, I actually did a study on

[00:36:46] Dr. Paulo Pinho: the incidents of somatization, so people presenting with physical complaints for psychiatric illness has gone up because of the fact that they oftentimes can access mental health or can’t access the appropriate type of mental health, or there’s social stigma as associated with mental health. Or you even look at mental health providers just being able to find a psychiatrist or a psychologist or a social worker that’s in your network

[00:37:13] Dr. Paulo Pinho: that can see you any, anything sooner than two months from now has been a significant issue. And you know, you can see where solutions like telemedicine, you can see where the ability to ask patients’ questions in a way that’s re recursive allows people, allows it to serve as a triage system that can identify those people that truly need to be seen much more rapidly

[00:37:36] Dr. Paulo Pinho: and those that perhaps can wait. You know, one of the stories I tell is about a family member of mine that had respiratory complaints and ended up getting admitted and nearly intubated because they went to an emergency department at the same hospital three separate times complaining of shortness of breath and on three separate times, got antibiotics as the prime modality of treatment for a diagnosis of pneumonia.

[00:38:01] Dr. Paulo Pinho: And it turns out that this person never had pneumonia and if they just looked into their medical records and accessed them in a way that was easier than having to look at pieces of paper or duplicate charts, you know, where there was cut and paste, where you had an active comprehensive problem list that was informatically coded into the chart

[00:38:21] Dr. Paulo Pinho: you could really pull together information and synthesize that information in a way to come up with a very thoughtful differential diagnosis about what was going on with this patient. It turns out that this patient didn’t have pneumonia. They had pneumonitis, and if they just went back to their gastroenterology records and they went back to their neurology records, they would see that in addition to respiratory complaints, they had GI complaints and they had neurologic complaints.

[00:38:44] Dr. Paulo Pinho: And it turns out that this was the first set of symptoms that this person was declaring themselves as having a rheumatologic illness with. So I, I, I think the ability to put information at the hands of clinicians in a thoughtful way, not putting the burden on the patients to tell their story every time they go into the emergency department or every time they see a new specialist.

[00:39:06] Dr. Paulo Pinho: I mean, that’s a huge absolution for patients of having to do that every time they, they seek care. And think about it, that the, the more complex you are as a patient, the more you’re gonna likely have to become an expert in your own diagnosis in order to basically transact your care because your medical chart has grown to the point that there’s thousands, tens of thousands of pages, and you need to be able to synthesize and summarize that so you know that the medications that you’ve been given have worked, and these are the side effect profiles that you’ve had, and this is the medication that didn’t work, and this is what ended up happening when you took this medication.

[00:39:39] Dr. Paulo Pinho: Like all of that information should be in a way that’s accessible so that it lends itself towards appropriate clinical decisioning, be it automation by machines or improved rate of, of speed by a clinician who’s able to look at that information on one screen and say, aha, this is what’s going on with this individual.

[00:39:58] Dr. Paulo Pinho: It looks like pneumonitis because they have GI issues and they have neurologic issues.

[00:40:04] Will Crawford: So that’s a good segue into talking a little bit more about equity and access. So, how both with improvements that we have made around standardization of healthcare data and of course these newer AI enabled technologies,

[00:40:20] Will Crawford: how do you see that helping bridge some of the gaps in healthcare access? Like we talked about it a little bit in the mental health context, but I’m sure there’s quite a few others.

[00:40:29] Dr. Paulo Pinho: Yeah, I mean, I, I think it comes with some pitfalls that I think we need to be concerned about. I think one of the things that I did in a study at one of my, recent job was I, I looked at data quality as it varied by demographic features, how as it varied by socioeconomic status, race, ethnicity, languages spoken, et cetera.

[00:40:52] Dr. Paulo Pinho: We have a significant challenge when it comes to data equity, um, in the United States, and not everybody has their data captured at the point of care in an equivalent fashion. And a lot of this has to do with ways that people utilize the healthcare system. I think in areas where there is provider mistrust

[00:41:09] Dr. Paulo Pinho: I think the emergency department tends to be a big source. I think you fail to create a longitudinal record that tells a full story. Even for chronic illness it tends to be an episodic care delivery model for these chronic illnesses. And so a lot of times you’re not really getting a robust data capture, and that’s, it’s one of the many reasons why you see such social disparities in the treatment of chronic illness is that some people receive their chronic illness care as a series of

[00:41:36] Dr. Paulo Pinho: independent acute illness representations. They go to the emergency department when they feel dizzy because their blood sugars are running 400. Instead of having proactive care that drives, that helps them so that their sugars are never 400. So we need to identify that there’s a substantial data equity piece.

[00:41:53] Dr. Paulo Pinho: When we’re looking at build, you know, machine learning models, one of the challenges that exist there is that, you know, your features may be the same for two diverse populations, but the way diagnoses are captured may be vastly different to the point that we may underestimate the prevalence in a population of a certain disease entity, or because of social stigma, it may actually present with a different ICD-10 code than depression, right?

[00:42:17] Dr. Paulo Pinho: They may have a series of somatic presentations of, uh, mental illness that we should have built-in ways in machine learning models that identify, hey, this person’s now been seen for palpitations, headache, abdominal pain, alternating diarrhea and constipation. Perhaps there’s a mental health issue that we need to address.

[00:42:38] Dr. Paulo Pinho: Perhaps that should be built into the way that we think about how this population in this geography or in this community tends to represent the way it, you know, mental health gets represented. And so I think the data equity piece is a big one. We need to understand that. We need to make sure that we’re considering the cultural context, we’re considering broadened data sources.

[00:43:02] Dr. Paulo Pinho: You know, not only some of the medical data, but also some of the social data is really important for certain populations. Um, we wanna do even stratified sampling within some of those populations to make sure that we’re doing things in a way that’s fair from a, an algorithmic standpoint. And at times where there’s data that’s missing, we need to

[00:43:21] Dr. Paulo Pinho: understand disease prevalence in certain populations and even do data augmentation until we get to a point where data capture is seen as more equitable for certain communities.

[00:43:31] Will Crawford: So you started your career on the practice side and then made the transition into clinical informatics, but never really stepped away from the practice element either. So for other physicians who are interested in getting more deeply involved with building digital healthcare technology and wanna make that transition either partially or completely into the healthcare technology world, what would you suggest they keep in mind?

[00:44:01] Dr. Paulo Pinho: Medical education’s evolved and has needed to evolve because of how much technology that exists in healthcare. You know, I think that different schools have evolved in different cases. Um, I would say that those students of medicine that are kind of going through the, the, the programming now take the opportunity to learn with people that are doing different things in healthcare.

[00:44:19] Dr. Paulo Pinho: And they’ll feel that because of the fact that you went to medical school, that there’s only one traditional way of practicing medicine and delivering, you know, value from a healthcare standpoint. I think there’s a lot that needs to be fixed in healthcare. Um, there’s a lot of policy issues that that PD addressed.

[00:44:34] Dr. Paulo Pinho: Um, there’s a lot of the different ways we transac healthcare. There’s a lot of gaps when it comes to care and ation, and it’s one of the things that I was kind of mentioning is previously, uh, patients don’t know how you use healthcare in the United States, like I had the opportunity to work in an urgent care center like it, it was a mixture of people that truly needed to be there because they had something that acquired urgent care.

[00:44:56] Dr. Paulo Pinho: And then I would say the other half of the people were people that probably either to be an emergency department and passed six of them along the way, uh, in order to get to this urgent care center. And there were, there were people that would come in and they had six months worth of the complaints that probably could be better dealt with with a primary care doctor.

[00:45:12] Dr. Paulo Pinho: People don’t know how to use the healthcare system. I think that we as clinicians can be empowered as of getting people to, you know, use it in, in a way that’s contextually appropriate. And then obviously, you know, in many of the conversations that we had, you’ve had, there’s a gap in, in, in terms of the resources that are necessary to provide care to whatever complex and ever aging, you know, population.

[00:45:36] Dr. Paulo Pinho: And so technology’s gonna have be the way to, to mitigate that. And so really identifying that you can provide value with your clinical know-how, in a way that’s non-traditional is really very, very valuable for, for, you know, clinicians of medicine to understand.

[00:45:54] Will Crawford: And then the opposite of that, for all the non-clinicians in the audience who want to get involved in healthcare technology and improving the way that we deliver care, whether it’s in, in this country or globally, where should they focus, you know, as they build their foundational knowledge of clinical informatics and interoperability in healthcare, AI?

[00:46:17] Dr. Paulo Pinho: Some of the more successful companies, um, when, when it comes to tech, new technology companies, some of the more successful companies in healthcare are first and foremost the health solutions company, and they have the, the, the key clinical pieces in place. Healthcare is nuanced, right?

[00:46:35] Dr. Paulo Pinho: It’s, it’s not like there’s a binary outcome for every compilation of tests. Not every test combination adds up to the same diagnosis. There’s a lot of many to one, one to many relationships that exist in healthcare. There’s a lot of interrelationships that exist and there’s no one way that a diagnosis presents.

[00:46:54] Dr. Paulo Pinho: There’s a lot of nuance to how they present. There’s not a one-size-fits-all treatment when it comes to, you know, hypertension. We often look at people with hypertension who have other comorbid illnesses, may respond to different anti-hypertensive medications, may actually have those anti-hypertensive medications treat some of their other comorbid illnesses if the right medication is selected.

[00:47:16] Dr. Paulo Pinho: So as people that are studying technology, studying data science, studying machine learning, AI, et cetera, understand that medicine is binary, it’s nuanced. Um, there’s a lot of drivers of medicine that are not just simply, purely based on, you know, how someone presents what diagnosis they have of what treatment they receive, but there’s a whole lot of interplay from social factors, et cetera.

[00:47:39] Dr. Paulo Pinho: Having clinicians on board to learn, knowing, knowing how to talk the talk and walk the walk of, of, of the clinician is important to adoption, right? Because there are stakeholders that oftentimes may get overlooked and these, these technology solutions get implemented in these, you know, hospital systems and provider offices, et cetera, and they’re the ones that could be part of your greatest success on a go-forward basis.

[00:48:03] Dr. Paulo Pinho: So, you know, I would say understand the limitations of AI, the biases that exist in AI for something as convoluted as as the medical sciences and learn from those medical scientists. The healthiest organizations I’ve been a part of, I’ve taught as much medicine as I’ve, as I’ve learned data science.

[00:48:22] Dr. Paulo Pinho: I’ve taught as much medicine as I’ve learned standards, right? Um, and I think that that bidirectional exchange of information really makes growing organizations and really deliver, delivers the best ROIs

[00:48:35] Will Crawford: So, uh, if our listeners could take, uh, one thing away from this conversation that we’ve had over the last hour or so, what would you like that to be?

[00:48:44] Dr. Paulo Pinho: So, I think the time is now. Setting aside adoption, setting aside, you know, some of the challenges that exist from the bias standpoint, setting aside some of the, uh, challenges that exists from patients and providers and technology solutions, et cetera. We need to reform the way healthcare is delivered in a way that’s equitable, in a way that’s thoughtful and a way makes the right diagnosis, prescribes the right treatment.

[00:49:11] Dr. Paulo Pinho: At the end of the day, technology enablement are really related. Um, and having the right organizational mixture of clinicians and technologists at a company is a vital key to success, not only of that company, but to the entire healthcare delivery model. Thank you very much.

[00:49:30] Will Crawford: Dr. Pinho. Thank you so much for being with us this I think that this conversation is gonna provide a lot of great context for listeners as they continue their own journeys in health IT.. This has been Hard Problems, Smart Solutions, the Newfire podcast. Thanks for listening and come back next time when we’ll be diving into interoperability strategy and digital health product management with podcaster Omar Muza.