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The journey to a next generation data-enabled healthcare delivery model
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Overview
Tune in for a discussion with Minal Patel, founder and CEO of Abacus Insights, on the challenges and promises of cloud transformation in healthcare. Topics include:
- DOT connector framework: leveraging technology to bring data together for analytics and other operational purposes
- Challenges from an organizational, transformational, and technology perspective
- Guidance for companies interested in improving their data usage
Topics: healthcare, cloud transformation, transformation, future of health, physicians, payers, patients, consumer, data and analytics, technology
Episode transcript
Find episode transcript below.
00:00:03:20 Welcome to Next in Health Podcast, I'm Jenny Colapietro, PwC’s vice chair for Health Industries, working across pharmaceuticals, MedTech, payers and providers.
IGOR BELOKRINITSKY:
00:00:13:22 And I'm Igor Belokrinitsky a principle with PwC Strategy& where I get to serve leading health organizations and help them with their strategies and operating models. And today I'm excited to have a colleague of mine, Ravi Kalakota, who's a managing director, who advises companies on cloud transformation, and he has brought a friend with him who he will introduce.
RAVI KALAKOTA:
00:00:36:16 Thank you Igor, let me start by providing some background and context to the conversation today. As you all know, data and analytics is a huge part of the future of health and wellness. Our clients are investing millions of dollars in modernizing and migrating to the next generation cloud platform.
00:00:54:04 The journey to a next generation data enabled healthcare delivery or digital front door model as you all know, it's not easy and is fraught with a lot of complexity. To talk about this transformation trend, we have Minal Patel, Founder and CEO of Abacus Insights with us today.
00:01:12:05 Minal is a very seasoned veteran. He has witnessed the problem firsthand, both as a physician and then as a payer executive. Welcome Minal. Can you start by defining the big problem in healthcare?
MINAL PATEL:
00:01:25:17 Ravi thank you for having me today and I'd like to add, in addition to being a physician and a payer executive, I've also been a patient in our healthcare system and struggled with the issue of data. The big problem we're looking to solve here is to really figure out how to help payers to become intra operable with their data.
00:01:43:17 We know that data is ultimately what's required at the right place for physicians, for patients, anybody to make the best healthcare decisions for their own benefit. And it's been a problem for many, many years of the last 10 to 20 years, lots of money has been thrown at it from the provider side, meaningful US dollars with the advent of the EMR.
00:02:02:11 But the payer has been largely underserved and I would argue that since payers have the most breadth of data when it comes to interactions with the healthcare system, absence of that data being shared and actually insights being created with the data coming from the provider system creates a real barrier to ultimately getting to what I think is the end of one and healthcare where each of us can make the best decisions about our health with the most relevant data available to us at the time we are given.
00:02:25:03 That's the problem we're going to solve.
JENNY COLAPIETRO:
00:02:27:07 Minal it's great to have you here as our guest today. Can you tell us a little bit more about Abacus Insights specifically and how your team is thinking about leveraging data?
MINAL PATEL:
00:02:36:23 Yeah, I'll give you that story, but slightly about how we got to forming Abacus as I am the founder of the company as well. So in addition to the experiences as an individual, I was also head of data and analytics for a large payer organization where I saw firsthand how hard it was to create any meaningful insight of all the data or assets that we had, all the claims data, the enrollment data, the pharmacy data from all the vendors.
00:02:59:15 So just basic business decisions that we needed to offer for our own beneficiaries was very hard to do, let alone sharing that data with third parties like our provider partners, analytics companies that would try to help us abstract value from that data, behavioral health companies that were doing interventions on our members, on our behalf.
00:03:16:07 And so the insight for us was that if you don't get the data right, all the billions of dollars that are thrown into those solutions that are at the end mile, it's essentially garbage in, garbage out.
00:03:26:08 And so Abacus was formed really to help payers solve that problem, having connectors into all the legacy systems that operate in the workflows of the pair. Again, the claims engines, enrollment systems, their UM authorization systems, many of these are decades old on premises and to try to get that data out and link it with all the other forms of data in the form of a patient, a member or a consumer, and really make that data usable.
00:03:50:15 That's really what our company does using that connector framework, leveraging technology to bring that data together and ultimately make it available for analytics and other operational purposes.
IGOR BELOKRINITSKY:
00:03:59:16 Minal that's a really helpful description and Ravi asked you about this big problem in healthcare, and it seems like everybody benefits if there is more data, if the data are more usable. Other industries seem to have solved this problem. And so why hasn't this happened in healthcare yet? Why don't we have a good hold of this data and are able to put it to good use?
MINAL PATEL:
00:04:18:21 Yeah, so first and foremost, I think a lot of people that have been in healthcare for a long time will say this and people that are now in health care will roll their eyes. And in this case, I think it's really true. Healthcare is different. The data that we have in healthcare yet has not been standardized in the way financial services and other industries have been able to standardize data.
00:04:35:21 And so until that day happens, it's going to require a level of investment at the level of system and domain that just creates a level of speed and inefficiency and speed to get to the place where that data are truly usable.
00:04:49:04 So when you think about healthcare data, and I'm talking structured data, let alone the all the unstructured data elements that are out there, until we get to a truly uniform standard mechanism to exchange data and interpret that data, it's going to be a long haul.
00:05:01:09 Now, industry bodies have tried it. You think about FHIR, the form of data formats that are clinically in orientation. That is a start. But again, a person having spent most of my life even as a physician in the payer world, FHIR doesn't go far enough to help for analytics purposes or understand domains of data that a payer cares about.
00:05:19:23 For example, employer, subscriber, broker. Those are key constituents to a payer’s data domain where unfortunately the clinical standards that FHIR and HL7 have abstracted have not gotten to that level yet. So we're on our way, but I think it's still 5 to 10 years, if not more, before that standardization truly becomes something that the industry can benefit from.
RAVI KALAKOTA:
00:05:39:03 So that's great, Minal for those companies who have identified this as a priority or an area they want to improve in, they're increasingly seeing that this is not a technical problem, this is an organizational and a transformation problem. So what is your experience? Why are companies struggling with this transformation?
MINAL PATEL:
00:05:57:17 Well, I would argue that it's a combination of both. I think it's a combination of an organizational set of challenges as well as technical challenges Ravi. In some regards, if you think about the world, typically it's a chief data officer or chief information officer or CTO that's been charged with trying to solve this problem.
00:06:15:04 They find themselves in this world where they're trying to solve the problem for a business purpose, but the business purposes have changed and I would argue with COVID have become even more fluid, right? So if the business targets are constantly moving over the lifecycle of a two or three year period, anchoring to one target is difficult.
00:06:32:05 The second thing is much of the source information is coming from systems that are sitting in the legacy environments typically on premises. And so you've got ever-changing business needs, you've got data stuck in an environment that are still 30, 40, 50 years old.
00:06:45:19 And then added to that, you have a series of tools and technologies in the form of the different clouds and in the form of the different innovators that are in the marketplace that are also constantly evolving. So when you put those three things together and then of course the fourth thing constrained budgets and just financial realities that these organizations have to deal with, it becomes really challenging to say, I'm going to do a data transformation starting from today, looking into the future and chart a course for the investments
00:07:10:17 I'm making today are not only going to solve the problems that my business has over the next 6 to 12 months. Let's face it, no one wants a three year investment journey, at least in this financial environment, but do it in a way that also allows the flexibility of the ongoing changes that are going to occur as time goes on.
00:07:25:15 And so this is an organizational and technical challenge that we see certainly the payer industry, almost every single company that we've had conversations with and speak to about why their cloud data transformation journeys have either failed in the worst case or just taken so much longer to create business value and certainly cost way more money than they ever thought it would.
JENNY COLAPIETRO:
00:07:44:11 Thanks Minal, it’s great to hear your perspectives, as you said, as both a physician, a patient, a healthcare exec, and as the founder of Abacus. Given all of that, what advice would you give companies who are interested in improving their data usage?
MINAL PATEL:
00:07:58:07 So goes back to addressing the problems is first and foremost, you think about business priorities changing. You've got to find a balance between on the one hand; business priorities are changing. I don't have a target to focus on. On the other hand, anchoring to only one specific use case often funding cycles are in payers and many businesses are done at the business use case level.
00:08:19:09 I have a business problem I need to solve, I'll get budget for it. Then I'll figure out how to work with all my stakeholders, whether they're technology stakeholders or others, in order to try to get whatever objective I want. The problem is that if you go too near focused, you'll solve that business problem, but not leave the flexibility for all the different changing requirements that are forthcoming.
00:08:37:13 And if you go too broad, it becomes a three year data transformation journey. So first and foremost, find a set of use cases that can show near-term value, but implement them in a way that gives you the flexibility that when use case three, four and five come to the table, you're able to supply that as well and that's a tricky thing to do.
00:08:54:21 But I'll give you a very practical example. When CMS passed the Patient Access API mandate, many, many companies went out there and said we need a compliance solution and they licensed compliance solutions that got them up and running for the 7/1/21 deadline for compliance with that specific mandate.
00:09:11:03 But then when the subsequent mandates came along, everyone scratching their heads saying, well, can I still use what I invested in or to extend that to meet the new mandate requirement? And the answer in many cases is no, because of just the way the initial implementation was done.
00:09:24:02 The approach that we've seen much more successful is to say, implement the mandate, but do it in a way that leaves flexibility of that data architecture to be used. Other use cases that come along the way and stars and heaters and population health analytics, etc..
00:09:36:09 And so the companies that followed that journey find themselves not only in taking the investment they did to solve the mandate problem in the near term, but also found themselves in a place where they can use the investments in a much more strategic fashion as new use cases and new business priorities came online.
00:09:51:04 And now that CMS has promulgated additional rules, find themselves in a much stronger position in order to meet those new mandates without having to reinvent the whole wheel and start all over again. So finding the right sequence of business priorities and balancing that from the short and long term needs that to us is probably the biggest advice to give to the companies that are going down this cloud data transformation journey.
00:10:12:07 And then the second thing I would say for companies that are going down the cloud transformation journey is don't go it alone. This is a really complex problem and there are organizations and technologies out there that can really help you accelerate your journey and not allow you to fall into those pitfalls.
00:10:27:05 The age old adage here is that many travel together, get further than those traveled alone. And this is a situation clearly where the amount of investment that's happened and specific capabilities and technologies really can help you get far.
00:10:38:12 And we are a case in point in that even in our own technology stacks, we leverage organizations that have made the investments to create a lot of the opportunity for acceleration that just allow us to leverage those technologies and piggyback and continue to further that journey. So that's the second piece of advice that I would give to those of you that are listening to this podcast.
IGOR BELOKRINITSKY:
00:10:55:22 Ravi and Minal, it was fantastic to have you both with us today to tackle this challenging issue and give some practical and specific examples of how it could be addressed more effectively and thanks for all the great work you're doing on this front every day.
00:11:12:08 For more on these topics and other health industry insights driven by policy, innovation and care delivery changes, please subscribe to our podcast and listen to the prior episodes as well. Until next time, this has been Next in Health.
ANNOUNCER:
00:11:31:14 This podcast is brought to you by PwC. All rights reserved. PwC refers to the US member firm or one of its subsidiaries or affiliates and may sometimes refer to the PwC Network. Each member firm is a separate legal entity. Please see www.pwc.com/structure for further details. This podcast is for general information purposes only and should not be used as a substitute for consultation with professional advisors.
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