A PSJH senior executive discusses the chief data officer role, how the health system is making better use of its data, what’s new on the analytics front, and how challenging PSJH’s innovation journey has been thus far.
At Seattle-based Providence St. Joseph Health (PSJH), innovation and digital transformation are key enterprise themes as the organization’s senior IT executives continue to push forward into new healthcare technology endeavors. To this end, about two-and-a-half years ago PSJH—a health system that includes Providence Health & Services and St. Joseph Health, with facilities in Alaska, California, Montana, New Mexico, Oregon, Texas and Washington—hired Vijay Venkatesan as the system’s senior vice president and chief data officer.
Venkatesan, who before coming to PSHJ was working at Northern California-based Sutter Health as the vice president of enterprise data management, recently spoke to Healthcare Informatics about what the chief data officer role entails, how PSJH is staying ahead of the curve to make better use of its data, what’s new on the analytics front, and how challenging the health system’s innovation journey has been thus far. Below are excerpts of that discussion.
What is involved in your role as chief data officer? What are the core responsibilities?
My role is about how to create a climate for leveraging data as an asset. And what does “data as an asset” mean? Are we able to land information, harmonize information, and then make it available for the various uses of the data that people have? For example, when you think about data in healthcare, it is about connecting the patient experience, how to create that patient experience across the continuum, and making sure it is available for the various data users. And then make sure that by using that information, we are able to drive better care quality and patient experiences on the other end.
Vijay Venkatesan
What is involved in “creating a climate for leveraging data” and what are some strategies for transforming the data culture?
In the healthcare setting, because of legacies or histories for how we have [developed] systems, there are various IT systems. You have multiple EHRs (electronic health records) and ancillary systems, meaning data is all over. So how do you create a cultural transformation of the data? The first thing we had to work on when I came onto the role at PSJH was figuring out how to get people to say, “Can we become shared producers and shared consumers of the data?” So if different data repositories exist across the system, how do you create a way to get that data in one place?
What we did was embrace the big data paradigm. We created a data lake where we invited our other data asset owners to contribute their data into the lake, in exchange for data they want or don’t have access to. So we created a culture of convergence, to bring data in one place and share each other’s information so that the collective organizations benefit.
The second step we are working on is creating a harmonizing data layer—think about it as your iTunes data catalog, where your albums in iTunes are categorized by rock, pop, alternative, etc. It’s the same idea. Now that we have data in one place, how do we create albums from the data? So an album could be a view of the organization’s financials, or a view of the clinical care quality side, or the revenue cycle, or the supply chain, or pharmacy. Think about it as albums with galleries. So that’s the transition we are in around thinking about data as an organizational asset.
Data and analytics is clearly a key part of what you do. In what ways are PSJH leveraging analytics to improve care and for population health purposes?
On the population health side, we have built a platform called Community Pathways to Health, which looks at Medicare and Medicaid populations at-risk, tries to organize them by the level of risk each patient has, and then we [find out], what are the right ways to engage those patients?
In that context, we are also embedding social determinants of health to create a risk score or predictive score to say, how do we look at our limited resources and what’s the best way to apply them across the patient population we have so we can effectively manage their care?
On the other side, we are also building a mobile-first strategy where we are looking at building a no-show app for our clinics, as no-shows are significant in healthcare since there is a big cost burden associated with them. So we built a mobile app running as compliment to the EHR where the urgent care staff can see a prediction on which patients might not show up for an appointment and then call them to try to get them to come in.
And on top of that, we are working on a model to see if we can “double book,” just like airlines double book seats. Can we find a way to effectively manage that slot better? And we are using artificial intelligence (AI), machine learning, and a predictive and mobile strategy to do all of that together. So far, we have reduced cancelations by 10 to 15 percent, which is significant for some of these clinics.
When thinking about this type of innovation and data transformation, how much of a driver is the transition to value-based care?
I think there are two disruptions in healthcare that are noticeable and significant. One is, within health systems, there is tremendous pressure on sustainability—how do we become sustainable in an era of lower reimbursements and value-based care in its truest sense?
On the flip side, we have a lot of industry disruption happening through technology organizations and companies, which is what I call “disruption at the edges.” What health systems need to do is recognize that digital health is here to stay and that data is a foundation for that ecosystem to be sustainable. The majority of care will be outside of your four walls, and though telehealth: we have to meet the patient where he or she is. That’s a real change itself. People who are practitioners of data and analytics must recognize that data itself will be varied and in different contexts, and we have to create a ubiquitous patient experience.
The other side is creating meaningful applications that leverage the analytics at scale. A lot of the analytics you see is very “point solution” still; it doesn’t create interoperability both in the data and technology sense, and it doesn’t create an integrated patient experience. At PSJH, we are very focused on that integrated patent experience, and working backwards from that, what are the right things to do on the data and technology sides to enable interoperability that delivers the integrated experience?
Is PSJH doing more now with AI and machine learning?
On all of these applications that I mentioned, there is a significant component of machine learning embedded in. As for AI, people consume healthcare not because they want to, but because they need to. So we need to make sure that when we introduce concepts such as AI and machine learning, we still focus on that patient-provider relationship. We need to uphold the integrity of that interaction. We try to think about where does AI benefit, enhance, or add value to that experience of the patient-provider relationship? That’s the business we are in. We are very deliberate about AI. You will hear in the industry that AI adoption is low in healthcare; but it’s not that it is low, it’s that we are focused on applying AI to the right places and where it’s appropriate because we want to maintain the integrity of the patient-provider relationship.
Can this innovation journey be challenging for providers who are not used to this type of change?
The way to think about it is, for health systems in general, it’s like Maslow's hierarchy of needs. You have areas in health systems looking for basic information and others that are ready to do robotic process automation. There are extremes and some health systems don’t know where to start. Do you meet the basic needs of food, shelter, clothing, and security, or do you go for that transformation?
At PSHJ, we have taken a deliberate strategy in that we need to both strengthen our core—how we manage our data—but we also need to transform for the future at the same time. This is not a linear discussion. You need to think about it as remediate and stabilize what needs to be stabilized, but don’t ignore the foundation building and the transformation of the future. So we look at the business problems we are trying to solve, and what’s the appropriate way to either advance innovation, advance the foundation, or to stabilize or stop doing something because it’s not value-enabling.
