The Organization for Responsible for the Multicare Health System based in Tacoma, Wash. It has been associated with a Open Site Data Analysis Platform Company called Tuva, and Multicare’s risk arm has invested in the company. Anna Taylor, associate vice president of the population’s health and care based on the value in Multicare Connected Care (MCC), and the CEO of Tuva, Aaron Neiderhiser Health innovation The open source frame opens on the opportunities.
Tuva Health, based in Salt Lake City, says that its objective is to establish the open standard for the transformation of health data and unlock the real data potential to transform health and medical care for each organization.
MCC is a subsidiary of absolute property of the Multicare health system that operates as an independent entity. MCC has established a clinically integrated network composed of doctors and other medical care providers, as well as hospitals, clinics and other medical care services, such as images, laboratories and pharmacies.
Neiderhiser is a former employee of Catalyst Health, and the co -founder Coco Zuloaga previously worked in Strive Health, who focuses on chronic kidney disease with a value -based care approach. The two are Squash players and argued to form the new company among Squash Games, said Neiderhiser.
HCI: Aaron, could the story behind the Tuva base and the problem that you and your co -founder were trying to solve?
Neiderhiser: Coco was leading the data team in Stive and I ran a team in Health Catalyst that was bringing clinical data and claims of the entire customer base in a single repository. It was one of the largest clinical and claims sets in the world, and we were using that data to perform benchmarking, train automatic learning models to generate pharmaceutical evidence from the point of view of real world evidence.
The more we talked, we realized that our teams were building exactly the same things. We need a common data model to standardize clinical and claims data. We need all these terminology sets. We need data quality tests for clinical and claims data. We need these higher level concepts integrated into the data, such as how do you define different therapies or health conditions or services?
The more we talk, the more we think we completely reinvent the wheel of these things. He took more time than this, but that is ultimately what became Tuva. All those who are dealing with the population medical care data, whether they are doing value based on value or if it is making real world from the pharmaceutical point of view, is dealing with the same problems, and there are no good tools out there. As an industry, we continue to reinvent the wheel, solving these problems over and over again. So, the idea behind Tuva is what happens if all this open source? What happens if we give these tools to people in the teams that need them? We could overcome these fundamental problems and start spending more time analyzing the data to obtain interesting ideas.
HCI: What are some of the implications from the perspective of a business model of open source?
Neiderhiser: We go through the open source route for two reasons. One is that we imagine working in other companies that discovered Tuva, and imagined that our things were behind a payment wall. If we built all these things and we couldn’t use it, we would only kill each other. Then we said it’s fine, we can’t do that.
The other thing is that the health analysis space is a very busy industry. There are some very large companies, and there are many smaller companies. There is also a long queue of consultants who do these things. Every time you do something in business, first of all, you must have a very clear idea of how you are different. I think that is even more important than the business model. We knew with open source that would be different. The bet is fine, it is more difficult to build the company at the beginning, because it is giving all this technology that is spending money to develop, and the early business model can be just services, right? But now we are reaching the point where we say openly all these fundamental things, and then we can build technology to solve more difficult problems that arise. That is the stage in which we are getting into.
HCI: Anna, could you talk about some of the things that Multicare’s team was not satisfied with her previous data analysis infrastructure and why was she open to look at something that they adopted a new approach?
Taylor: All our bases are based on the economic model of rate for service, and we are trying to perform both in rate and value. We needed an infrastructure that serves our ability to have a P&L for both models, so that when we are executing the volume through the Emergency Department, we know how our lives based on risk affects, and that is a data infrastructure different from what we have today. We knew we had to transform ourselves to survive. We are a non -profit health system in the state of Washington, and we want to remain independent. To succeed, we needed to be able to execute both financial models.
Tuva was an answer for us to clearly understand what architecture was underneath. It was visible, transparent to us, and it was a low cost option. We have contracts that we can execute through other services that allow them. We may have a fully capitted product, as our employee health plan, where we own the final result, which we execute through a platform as an innovation, say. But for the contracts that may not allow us that capacity, we needed a solution in which we could house all this data and put the agents on top so that it is plugging and playing through the infrastructure and the data ecosystem. We wanted a center of the universe that did it for any type of contract that we would have instead, both the service rate and risk -based contracts.
HCI: Did I see you cited saying that you really considered building something internally before finding Tuva?
Taylor: Yes, that is correct. We said, ok, there is nothing that can buy that will give you this transparency. It is a black box. We wanted to build our own infrastructure, because there is nothing to serve both worlds in this sophisticated way and allow us to put it into something modern, such as fabric or aws, so that we can also take advantage of those services. So we were going to build it ourselves, but then our actuaries learned about Tuva, and our data scientists took a look, and it was the perfect combination for our problem.
HCI: Could the open source nature of this allow the things developed in a health system to be used by other health system partners without having to reinvent the wheel?
Taylor: Deep in my heart and written in Multicare’s values is the fact that we do not want to compete in this. What we want to compete is how care we are providing the community. As Aaron described, health systems are solving this 100 times. We no longer need to do that. We can have this semantic and shared infrastructure that we have the ability to customize our business culture, and that is what will give us that advantage, because any customization we do is bring to a better service, better health. But the basic concepts must be shared, because we should not compete in that in the market.
HCI: anything else you want to add?
Taylor: We are all trying to solve this really difficult problem with much less resources than before the pandemic because we are still in deep recovery mode. It is incredibly energizing to find a place that has an answer other than a million dollars, because that seems to be the price for each agent with which we are trying to solve medical care: one million dollars.
We hope to have some excellent results for the end of the year. Until now, we display the data warehouse in five weeks. We were in production, we executed contracts in three weeks and we had them in QA, and we are doing a data analysis out of there. Then, in a matter of eight weeks, we had a business data warehouse, which is surprising.
