In this episode, Neal Singh, CEO at Caradigm discusses population health management, AI and emerging data sources, especially social determinants of health.
Welcome to The Big Unlock where we discuss data analytics and emerging technologies in healthcare. Here are some of the most innovative thinkers and health care information technology talk about the digital transformation of healthcare and how they are driving change in their organizations.
Hello, everyone this is Paddy, it’s my real pleasure to have on this podcast my very special guest Neal Singh, CEO of Caradigm. Neil, welcome!
Thank You Paddy, I appreciate the honour to attend your podcast and happy to answer any questions today.
Wonderful wonderful let’s start with this for the benefit of our listeners. Tell us a bit about Caradigm and what problem Caradigm solves for healthcare today.
Sure, so the Caradigm Paddy, was set up in 2012 as a joint venture between Microsoft and GE and from day one you know we’ve been set up as a population health software company and that continues to be our strategy and focus. Our key differentiator is that we provide a tightly end-to-end highly integrated enterprise population health portfolio of applications both with handling data analytics as well as care coordination. Specifically, in the context of data we offer real-time data analytics and in terms of you know getting data in from multiple systems in a real-time basis and taking action on it versus just doing traditional ETL mechanisms to get data once a month or once a quarter. And other differentiator that we have is we actually get data across multiple spectrums of healthcare so be it clinical claims, financial and now we have even extended deeper into social determinants of health. And what we have found historically is many vendors just focus on just clinical or just claims and I think having the super set really allows our customers to get a significant leg up and in terms of being able to help our patients move towards the population health goals. Specifically, in the context of social determinants of health you know we recognize the importance and value in the context of social economic and environmental factors which determine about 50% of the overall health of the patient. And at least 25 cents of every healthcare dollar is being now spent in treatment of conditions resulting from potentially changeable behaviours. For example zip code has a strong predictor on a person health than even the genetic code in some cases and the National Quality forum CDC and who all acknowledge the importance of social determinants of health.
Right, right, I’m going to come back to the different data types and the emerging data types in a minute but you know you defined Caradigm as a population health management company. How has the definition of population health management changed over the last couple years or has it changed at all.
Yeah, absolutely I think you know in fact I will say it’s not changed but it’s solidified. It’s probably the word to use what we’ve seen specifically is that you know we work very closely in conjunction with class research and class research has defined a definition of population health management which is the process of proactively monitoring and caring for defined patient groups. I think furthermore drawing on healthcare organizations and their leading top health vendors that we have participated with them as well and that they have assembled a framework. And this framework really has seven core aspects of capabilities which is aggregation, analysis, care coordination and health improvement, administrative and financial patient engagement and clinician engagement. So these are the core seven areas they’re defined on a framework. I think we’ve even tried to simplify it down to kind of I would say three core capabilities which is if you want an effective population management you really got to focus on data control, on the healthcare analytics and care coordination and engagement to deliver solutions in this category of applications in the population health space.
Right, right, so so it sounds like Population health management as you define it or as you stated it the definition has solidified so people have a better understanding and there is some common framework that people are applying to define population health management and so there’s a common language in the marketplace that is emerging it which was not the case a couple of years ago. You know people may you know they meant different things when they said population of management. So you know obviously the data sources you refer to some of them and it’s key to population health management to develop a holistic view of patients and you rightly mentioned social determinants of health zip code as an example as one of the strongest predictors of health and wellness on populations. So you know the data sources are emerging they are kind of in structured and unstructured formats and they’re they look a lot different from your standard structured electronic health records you know you’re talking about social determinants, you’re talking about IOT data, you’re talking about genomics data, all kinds of data sources. What do you see are the biggest challenges the industry is going to have to overcome in being able to harness all of this data to generate the kind of insights you need to effectively be a published in health management company or effectively manage population health if you’re a health system.
I think this is an excellent question, I think there are a few pieces. Number one is you need to have systems infrastructure and capability to be able to aggregate you know the growing set of data pieces right whether it is you know like I mentioned earlier and there’s the clinical claims financial expanding to social determinants of health, you mentioned genomics and IOT. I think we will continue to see data sources increase or even a much faster accelerating pace. So you need a system that can scale and take in different data types and that I think is one key aspect of what you need in any platform to be able to move forward and provide population health management. The second piece is as these different data sources keep coming in how do you start not just aggregating the data but how do you pull that data in and make that available throughout your entire application set so that you can start reaping the benefits in a very seamless manner. So I think those two pieces are combined at the Meta level important aspects of how you basically deal with data. Then getting to the next part of the question which is you know how do you how do we think about these different sources of data for example you mentioned genomics I think genomics is early on it’s a key part of precision health in terms of imposition health will end up with and I see basically more of population health you know morphing into basic aspects of precision health over a longer period of time but I think right now genomics is it’s commercially not viable, it’s the basic, it’s still a very expensive tool and I think as that as the prices come down as the applicability comes up becomes more widely usable I think it will become a key part of data just as what we’re talking about today in the case of social determinants of health you know beyond the few data points and mention earlier around social determinants of health what we’re doing is you know we have taken a much more broader approach to social determinants. For example you know like many application providers what they do is they take they ask a few questions and they display the answers of social determinants of health. I think that’s very much at the periphery level it’s a good marketing message but it doesn’t really add any value. So what we’re doing is really upping the game in terms of taking these large data sets and pulling them into our system normalizing them and then morphing them in terms of different application scenarios. So for example when we do stratification of risk meaning we’re trying to figure out, out of these you know millions of patients which one stuff, the provide should focus on we basically we build our algorithms which are driven with AI now as a mix to really drive towards you know patients who have a higher socio-economic risk profile we use social determinants of health to help drive a risk stratification you know before we start making actions in terms of clinical side of the equation. In care management we are trying to understand the socioeconomic profile of a patient before engaging with them. We are dealing we are tailoring the goals and intervention for the care of plans based on data that drives through the social determinants of health. In quality improvement we identify potential barriers to closing gaps example transportation gaps you know somebody doesn’t have transportation access how do you how will they be able to close the gap in care and of course knowledge have basically providing insight to providers about the patient through the gathering of this data. So I think there are many aspects even some other aspects that come into play like identifying communities who need a particular resource for or basically community health worker who wants to provide home visits to care managers and and and in location and dialysis facilities as to where the availability is so there are lots of things that we can do with social data but the main point is how do we make that available seamlessly in the applications as part of the workflow versus the care manager of care coordinator has coordinated having to figure out a hey here some social data let me try to figure out how to integrate that into my day-to-day life.
All right when we talk about all these new and emerging data sources we have to talk about two things one is the I-word interoperability right. How are we gonna solve that so that’s one and then the other thing you already touched upon this whole notion of you know marketing message versus real substance to what you’re doing and in that context you know AI, everybody is talking AI. I know these are slightly unrelated but I would like to do you know touch upon the you know are we going to are we going to see an interoperability solution I mean is fire going to be the solution what is the solution and and how are you approaching it and then tell me a little bit about what do you think of AI you know is it hype is it real you know what is it you guys doing?
No sure I think that’s an excellent question especially given the conversations happening today in the market and both these topics. So I think from a Caradigm perspective we welcome advances and improving interoperability amongst different systems you know we know that certain EMR vendors have been hesitant in sharing data and new protocols like fire and I helped break down those barriers I think that should lead towards more comprehensive patient records, improved communication ultimately improve patient outcomes. Now one file can provide benefit it is better utilized towards what I would quantify as low to medium volume transactions. And so when it comes to high volume bulk transfers of you know megabytes of data which we do very regularly for large population of our providers I think you still have to resort today to the traditional web services and ETL mechanisms to drive larger volume and I think the other portion is I think I love the fact that Apple has now you know made fire an interface for individual patient records and I think that’s a first example of how companies like Apple are going to help try the echo system forward and interoperability now and that portion of course still focuses on an individual patient getting access to the record from a set of providers who basically agreed to partner with Apple. I hope that that ecosystem continues to grow because I think it’s super important for healthcare transparency and even wellness that patients have access to all the records seamlessly and I think that that would be a great outcome for patients.
Now getting into the AI piece you know it’s a very good question in terms if it is hype or reality. I think you know AI is one of the next key advances in healthcare. You know a solution that incorporates machine learning, deep learning we can provide you know better analytics to organizations well I think it’s moving from what I would say being hype to now showing early promise of delivery. What we are doing specifically before I kind of deep dive into that pieces you know what we’re doing specifically we have taken an approach to AI which is different than lot of the you know healthcare startups that are trying to formulate algorithms around AI or or even make statements around AI. I think many AI vendors position themselves as the AI company or deep products that you have to buy or the thing that you have to buy and then figure out how to work with your IT organization to enable within your workflow I think we are taking an approach that you know AI needs to be you know seamlessly infused to our system it needs to be ambiently embedded across our application workflows and customers should not have to do anything special to buy or enable AI in order to beat the benefits or even know the existence of the AI for that matter.
Invisible in another words. Absolutely, absolutely I mean that’s where and really we need to focus on not AI as a technology but in terms of what outcomes and ROI we can reap for our customers I think that that’s really where we’re focusing in terms of our investments and in terms of in terms of our outcomes.
That’s all well said Neal, that is so well said because I think a few years back we had the same thing with big data right as though big data was the solution or you know was the be all and end all but we’ve seen that over time you know it just permeates through an entire analytics infrastructure and it’s no longer visible. It’s invisible to the point of it seamlessly being incorporated into all advanced technology solutions right? Would that be a fair statement?
Yeah I would agree I think you said it articulated extremely well that is exactly what we are we would love to see and so what the thing is you know we have been investing we have got a partnership at Microsoft. We infact doing a pretty big launch around you know intelligent population health as we call it as how do we bring AI into population health so there will be a pretty big launch happening next week at HIMSS around what they’re doing in AI and specifically in terms of what scenarios we are enabling within the work flow so whether it’s bringing intelligence into, how we stratify the population of patients or bringing intelligence into how care coordination assessment workflows becomes smarter and better so you know we have we have we have basically enabled AI in our system we don’t plan to charge customers for AI we plan to basically deliver differentiating value proposition where AI make our systems significantly smarter for our customers and drive significant value for them in these workflows and to be honest we are early on I think the industry’s early on but more importantly what we’re doing is we’ve become very I would say very thoughtful about working with real customers and real data to identify real outcomes I think that’s important because you know sitting in a computer lab building AI is an interesting technology experiment but what we are doing is we are working with real customers and then enabling these as part of the work flow so that the next customer basically gets the benefit of that enable meant without either having to pay for it or you knowing it that it exists.
Awesome, awesome I just love that whole position that you stated I think that is so important for your customers and also your competitors and peers in the industry to understand. Ultimately it is about what it does it’s not about be-all and end-all in itself that’s wonderful. You know for you were you were one of the contributors to my recent book the big unlock and once again I must thank you for taking the time for speaking with me and providing me with the input so the one thing that you had said there that stuck with me. You had said that health systems are going to find it increasingly hard to live by the rule that they will operate within a single EHR system for the benefit of our listeners and for my own benefit I’d like to hear you say it again what should health systems be doing those were locked in yesterday from the EHR what you know what do we have forward for them.
That’s a good question so the concept and motion of a single EHR I think that there are there are certain hospital systems that are locked into a single EHR but you know as even single EHR hospitals you know are now rethinking that strategy because as a lot of M&A activity is happening it’s nearly impossible to keep buying hospital systems and then trying to spend a large chunk of you know IT dollars and just bringing people into a single EHR system. But I think what’s made it even more I would say harder to think about everything sitting in one EHR is this motion around accountable care or around clinically integrated networks and so you know if you’re taking on an accountable care contract and especially as part of the accountable care contract whether it’s a commercial or a federal contract you know you may have to provide care with other organizations and they basically may not be in the same EMR system and they may not even be of your size in terms of you know if you’re a large enterprise player partnering with another enterprise player partnering with smaller clinics right you can’t have the same EMR everywhere or even try to say that look we can’t provide care until all the systems get on 20 MR which can take many many years. So really I think in that world if you want to be successful in this new payment reformed model of value-based care I think you have to really think about how can you operate in a environment with multiple systems. Whether they are EMR, whether they are claim system, they are financial systems, they are social data systems. I think you really have to live within this world so you really need a system that can actually help you across the boundaries of data but also more importantly cross the boundaries of your enterprise organization and be able to scale to that level of carrying data seamlessly so that’s really what you can do is say I can provide care. I’ll give an example you know let’s say you know I’m providing care for a patient and I’m a care manager and you know one of the things I’m trying to basically do is make sure that I can provide the maximum amount of high-quality care for the patient outside the hospital so they can do right things wellness and care and prescription perspective to take care of their care. But then my patient basically shows up in an ER system for some medical situation you know and if that ER system sits outside my HR then basically I would never know that happened but if you’re in this across enterprise data scenario in our systems what we do is we alert the care manager hey your patient showed up in this ER today and no matter what EMR system was there and then what happens is they can follow up with that patient later on during the day to find out what happened why did they have to go to ER. Again this is how you can prevent a lot of unnecessary ER consumption and which is very expensive right so that’s an example of how you really have to think across one EMR and across one data source.
Very interesting very interesting so you know you mentioned value-based care right so we know the industry’s shifting towards value-based care but maybe it’s not happening as quickly or as rapidly as we would like it still a lot of fee-for-service arrangements are there if you have a little bit about what you see in the current policy environment and especially as it relates to the shift towards value based care what does it mean what are the implications for your business and when you should prepare it?
That’s an excellent question I think you know despite the uncertainty at the federal level I think the shift to value-based care has not stopped I mean it’s continue to move in that direction because ultimately the move towards value-based care is really around basics and principles of economic right.
You have to really kind of you can’t continue in a world where you’re basically not focused on outcomes driven payment systems and continue to increase health care costs along the way you know. I think people are moving past the uncertainty and even with the changes. We have seen two major shifts one is more and emphasis from the private sector side health plans and employers in particular and secondly we are seeing an increase in breadth and diversity of value-based care programs. For example MAAPE in a bundle payments and the likes of that so I think that portion that will continue to become more and more prevalent but then also I think the federal side we are seeing more movement from voluntary from mandatory to voluntary programs. So I think they will continue to be growth and but I think especially in 2018 we have seen the shift you know while 2017 especially the second half seem to have stalled we’re seeing a significant acceleration happening now in 2018 and that and that’s purely based on what we are seeing from a commercial pipeline and a cells of perspective. The other portion I think is that you know I think organization sees an opportunity to become competitive in a market where the competitors may not be moving as fast so so while we see lawmakers continue to battle it out I think we face one fact that value-based scale is here to stay. Providers, so basically you know push forward with what we call is the no regrets strategy which means provide prioritizing efforts to drive more consistent efficient and coordinated care integrating the IT systems to support accurately forecasting patient risk lowering cost structures and building deeper relationships and loyalty with the patients and I think that no regrets strategy will help you no matter whether you’re in people service or value-based care.
No regret strategy, I like that term okay last question for you what are your 2018 priorities for Caradigm.
Yeah we are focusing on several things I think that the main thing that we are trying to do is with trying to focus heavily on what I would say is rapid time to value and what we mean by rapid time to value is how can our customers get, you know time to value very quickly from our system so when we deploy systems how quickly can be have our systems go live but live is just a milestone how quickly can our systems be adopted as more important and then more importantly what is the outcome and ROI our customers achieving so we focus now very heavily on that time to value equation. So it used to be TCO in the old world of total cost of ownership at a company level across the board every single employer the company’s focus around customer outcomes and driving time as a key factor in terms of getting the outcomes for them in a very rapid way and then the second piece in that same notion of time to value is you know we have traditionally focused on enterprise customers with fully integrated systems that have a single platform and we’re able to service application or a single platform to drive time to value for our enterprise customers. We have now you know launched out solutions that are very quickly adoptable with pre-packaged solution that you know smaller, mid to small ACOs can adopt and get rapid time to value. Literally we’re talking about you know goal eyes that can happen within 30 days of signing a contract and then that I think is very significant and very fast which is kind of unheard off in the healthcare industry in terms of how we can write fast value for our customers. The third piece really is around I think we have to continue to focus on innovation. But the way we are thinking about innovation is very rapid so you know we have a deep technology partnership with Microsoft you know. A primarily because often our roots back to the joint venture with Microsoft where half the company came out of but also in terms of really you know taking advantage of the deep talent that Microsoft has. So for example Microsoft has made some very significant investments around a visual analytics so now we’re going to launch what I call as Power BI for healthcare which is basically how can health care organizations get you know fast time to value around self-service analytics without having to know the understanding about how to do plumbing and hosting and then taking care of security and HIPAA compliance in a very seamless manner. So I think that’s where we’ve kind of put together it with Microsoft’s help in building out the Caradigm visual analytic solution. AI is a good example where we’re using Microsoft technology again not a standalone as the thing that you buy versus as a seamlessly integrated capability throughout our entire workflow and then you know the social determinants of health I think we are doing some really cool and interesting stuff and in all these areas while we have done a lot of technology platforms when the enabling use cases that we’re launching at HIMSS many of them as customers I think will the next 12 months you will see us creating a very significant volume especially in these three areas for having customer value oriented solutions delivered to the market.
Awesome so in one short sentence would you say the mantra for this year is customer success?
Oh fantastic Neil it’s been a real pleasure speaking with you as always and thank you for your time and have a wonderful HIMSS. Look forward to seeing you there. Thank you Paddy, you have a good one. I look forward to seeing you there as well.
Neal Singh , CEO, Caradigm
Neal Singh is the CEO of Caradigm and serves on the company’s Board of Directors.
Mr. Singh has spent more than 25 years working in enterprise business and software leadership roles. Prior to becoming Caradigm’s CEO and President, Mr. Singh served as Chief Technology Officer, where he led the strategic vision and execution of Caradigm’s enterprise portfolio of population health solutions. A member of Caradigm’s executive leadership team since its inception, Singh joined the company after spending over a decade at Microsoft including his last role as general manager of Global Development at Microsoft Dynamics, where he led a global team overseeing business strategy, product management and engineering. Throughout his career, Mr. Singh has held multiple executive leadership roles, and is recognized as a thought leader for healthcare technology.
Mr. Singh has a PDEE in electrical engineering, a Master of Business Administration from Phillips University and executive education from Harvard University.
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