Making Rounds: Leveraging analytics to create efficiencies [Podcast]

For years, the tech industry has relied on millions of terabytes of highly specific data to deliver faster results, increase efficiency, and create a more personalized experience for its users. The healthcare industry is currently sitting on its own trove of data that, when activated, will revolutionize the clinician and patient experience. Applying modern analytic tools to these data can give health systems the increased efficiency, avoidance of burnout, and improved patient care needed to combat the Big Squeeze.

In this episode of In Network’s podcast feature Making Rounds, Head of Thought Leadership Dr. Jerome Pagani speaks with Nordic’s Digital Health Practice Leader Kevin Erdal and Performance Improvement Practice Leader Wally Ward. They discuss how enterprise data can help ease the strain on healthcare systems, how organizations can turn data into a true strategic asset, and how modernizing business intelligence systems can create the foundation for real-time insights and decision-making.

Listen here:


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Show Notes:

[00:00] Intros

[01:33] Factors contributing to the Big Squeeze on the clinical and operational front

[02:57] How healthcare systems can use data to find improvements

[05:29] Tools health systems will need to make use of data

[06:51] Using real-time data to help make clinical and operational decisions

[07:37] Activating the data

[08:43] Specific use cases of utilizing health system data

[11:42] The future of dynamic scheduling experiences

[15:50] Pricing transparency in healthcare



Dr. Jerome Pagani: Kevin, Wally, thanks so much for joining us today.

Kevin Erdal: Happy to be here.

Wally Ward: Good morning.

Dr. Jerome Pagani: So the myriad factors affecting health systems, which we've kind of dubbed the Big Squeeze, they're having an impact on both clinical and operational fronts. Wally, how are those health systems being affected, and what sorts of initiatives are we seeing to address those impacts?

Wally Ward: Well, Jerome, you know, we're seeing a lot of impacts on the health system today. Everything from labor shortages to the crush of new diseases and chronic conditions coming out of COVID. We're seeing a lot of patients who have pent-up demand from not being able to get services while the pandemic was going on to inflation and rising cost of healthcare. So everything basically that's happening in the market outside of healthcare is also affecting healthcare to a very large degree. So that's causing all of the provider systems to look for alternative ways to provide services to patients, either through virtual care, what we call digital front door, where they access in a different way or any other ways that they can use technology to try to deliver more services with less staff.

Dr. Jerome Pagani: I'm hearing that efficiency piece really trying to help people operate at the top of their license, deliver high-quality care to as many people as possible, with as few staff as possible.

Wally Ward: That's right. It's an ongoing problem that all the providers are trying to solve.

Dr. Jerome Pagani: And Kevin, how can enterprise data help these sorts of issues?

Kevin Erdal: Yeah. So health systems in today's world are sitting on a trove of data and have been for a while. So we really want to start to understand how we can leverage some of that operational data in-app, or within the application, within the health systems application specifically, whether that's a med dispensing machine, whether it's an EMR, whether it's a combination of all the above, and then start to understand what impacts is that having on the labor staff, for example. So can we start to look at the populations of patients that we're caring for a little bit differently and maybe leverage some of those virtual visits differently or more broadly that while they started to reference, but we're also starting to look at different ways that we can leverage that non-application data as well, or some of that data that is generated outside of the health system. In some cases, that's going to be your claims data, and we've been talking about that quite a bit. And how can we learn some additional insights about where populations of patients are going maybe outside of the health system? And that health system might assume they're caring for those patients because they're within their community or they're within their region, but for whatever reason, those patients might be going elsewhere. So we can derive some insights there to inform some of the broader strategies. And we're also starting to see a lot more data consumed by some of the patients and the members, whether it be the IOMT data or just some of the expectations that patients are wanting to see more information from their clinician in near real-time.

Dr. Jerome Pagani: So it sounds like those data can provide insights on both the clinical and operational front.

Kevin Erdal: Yeah, absolutely. And starting to stitch that together over time is exactly what we need to be working towards. And a lot of folks are starting down that path right now.

Dr. Jerome Pagani: And what about EHR data itself?

Kevin Erdal: Yeah. So that EHR data are really, that's kind of that in-app data that I referenced earlier. So we're really good at what I call some of the pixel-perfect kind of reporting. So when we're documenting information on a particular patient within a specific module or a specific department such as ambulatory or cardiology or what have you, we've gotten really, really good within healthcare to surface some of that specific information within that application, within that module. So that's fantastic. But there's a lot of data outside of those processes that we can also derive some additional insights from to support, whether it be throughput or workflows or labor shortages, things of that nature, that we want to make sure we're combining with that external data we just talked about a minute ago, that claims data or even some of that IMT kind of data as well. So it's not just in-app data that we've gotten really pretty good at, whether it be your EMR or that dispensing machine, but also some of that data that we're combining now with that quote-unquote external data.

Dr. Jerome Pagani: Yeah. So that's part of that trove of data that you referenced earlier. What sort of tools do health systems need to have in order to really make use of those data and do the kind of analytics that will provide the insights they're looking for?

Kevin Erdal: Yeah, we need more tools in the tool belt to a degree, but we also need to standardize a little bit. So if you look at any of the industry-leading researchers right now, they're suggesting analytics is still a top three to top five priority for a lot of the health systems specifically. Not so much on the payer side in today's world, but specifically within the health systems. And we refer to that as business intelligence modernization. So we want to make sure that we're shrinking as much of the technical footprint as possible. So if we have multiple tools doing the same exact thing, how can we consolidate into one tool, and that we're also leveraging to the best of our ability the tools that the applications are providing, whether it be an EMR provider or whether it be a patient scheduling application, we want to make sure that we're using that for operational kind of reporting, but then we're using some of the Power BI Tableau type solutions for that true business intelligence. So that's the visualization layer. That's all predicated on some of the things we've talked about in the past, Jerome, to make sure that we have a solid data foundation. We can then roll out some of the business intelligence tools based off of trusted data in a repeatable and a consistent fashion with both that application-oriented data and that external data that we've been talking about a little bit today.

Dr. Jerome Pagani: Okay. So let's say we have a health system that's modernized their BI infrastructure and they've consolidated reports and they've created dashboards. What's the next step?

Kevin Erdal: Well, two things, really. We want to make sure that there is a proper training, that people are not only utilizing the tools, but they understand the data that they're interpreting. So that’s, that's kind of a key step. But then in addition to that, we want to start getting as close as possible to quote-unquote, real-time data. And I'm using quotes there because in some cases that's actually event-driven data where an event happens within a health system that can then trigger some form of action within the tool itself, or to send an alert maybe to a clinician or maybe to a care manager or in some cases even to the member. And then that can start to inform some of the workflow and some of the other activity that Wally’s been talking about to date as well.

Dr. Jerome Pagani: So Wally, how do we see that actually playing out in our clients?

Wally Ward: Well, the real key to having the data is being able to activate the data. And by activate the data, what we mean is use that data to make decisions and change the way that you deliver care to patients to improve the patient experience. So, for example, in a perioperative space, you may use data around workflows in the operating rooms to better schedule your operating room so you get maximum efficiency out of these operating rooms. You don't have downtime. You use the data to figure out what are the right level of physician preference items you need in the operating room so that you're eliminating waste within the operating rooms and using that data really across all parts of the organization to affect the way that you deliver care to your high volume patients with chronic diseases and also how you deliver better care to your low-risk patients in a more effective manner while you're looking at how you deliver care to the high-risk patients.

Dr. Jerome Pagani: So Wally, you mentioned that, that phrase of activating data, which I love, can we talk about how we use that sort of activated data and combine it with people and technology around other specific use cases?

Wally Ward: Sure. So, for example, we're seeing a lot of health systems now who are looking for ways to get their patients into their system. We call it digital front door or patient access. How do I get people into the system and treat them in a more effective manner? And I can use data to determine how I schedule visits, how do I get maximum efficiency out of the physicians and providing visits to patients looking at the right levels of turnaround? How do I start to have different levels of providers provide the services based on the condition of the patient, based on the data that we've seen for that patient. So get our clinicians working at top of license, whether they be physicians, PAs, nurses, how do we get the most effective use out of the staff that we have by using the data to target where those areas that we really need to focus?

Kevin Erdal: And this is the really exciting piece right now and why it's so exciting to work with Wally and his collective team on a lot of these initiatives. We used to think of data and come up with a conditional format in kind of mentality where we would analyze a population of patients and maybe categorize people, you know, red, yellow, green kind of concept to say, Hey, this patient hasn't been connected in two weeks, in two months and whatever the scenario may be. Well, what Wally just mentioned in the activation and when clinicians or care managers or people caring for patients start to see some of this data in real-time and they know exactly what to do when a patient comes to the top of their queue and actually connect with them, now we're starting to impact patient care. It's not just a patient on a dashboard anymore with a pretty color next to it.

Dr. Jerome Pagani: Yeah. So it sounds like you're really talking about bringing the patient's care journey to life and, and using those data specifically for that. Are there other ways that we can be thinking about patient engagement and helping them to manage their health in between those checkpoints?

Wally Ward: Well, part of the data we need to look at is not only clinical data, but also data related to the patient. What languages do they speak? What are they conversant in? How do we communicate with them most effectively? Is it through email? Is it through text message? Is it through some other form? The patient today interacts with the health system in a lot of different ways. Not everybody is always going to go in. You may have a telehealth visit, you may have some other type of virtual care that you're doing with the patient, and you use that data to figure out what's the right way to interact with that patient to get them the most effective outcome from their visit.

Dr. Jerome Pagani: You know, one of the things that has consistently frustrated me is the scheduling experience in healthcare. And I keep wondering why it isn't like booking an airline flight or some of the other scheduling experiences or Open Table or one of those. Is this something that's coming to healthcare?

Kevin Erdal: It's here to a degree now, right? Depending on what system you are interacting with on a regular basis. And I think some of the complexity that Wally just hit on, making sure that we have consistency around the way we schedule patients and we have consistency around schedules for physicians. We have consistency around various departments, right? Because it's going to be a little bit different for an ambulatory setting versus an inpatient setting versus a specialist. So we're starting to see some of that, some of net new technology enabling that behavior. But like while Wally mentioned, there's a lot of workflow that has to be modernized and updated to even enable that core activity.

Wally Ward: And we're starting to see new technology now that is actually allowing the patient to schedule their own visit. So instead of me calling the physician and finding out, okay, I can see you on this day at this time, which may not be convenient for me, let me go in and schedule my own visit at a time that's convenient that I know I can make that time and I can be there. And it provides much better throughput for the provider system because you don't have as many missed appointments. Using this data has shown that we have a lot of reduction in missed appointments, people being late, etc., because we're allowing them to schedule their visit at a time that's convenient for them and that they can keep up with.

Dr. Jerome Pagani: What I love about the way you're talking about this is that it's so different from the way we started talking about the digital front door, which is as a portal that people could go visit. And it was an entryway into interacting with the system. And what you're talking about is something that's really dynamic and made for the person, almost like a custom-fit shirt or something that is functional and flexes with the patient's needs.

Kevin Erdal: Yeah, the portal isn't for everybody right? There, don't get me wrong, there are a lot of fantastic use cases and a lot of great success stories around interacting via a portal. I use it personally, right, on behalf of some of my kids and chatting with nurses and things of that nature. But when you start to get into more urgent or near real-time needs that some of our patients and some of all of us need as patients, we need to think of those things a little bit differently.

Wally Ward: And the key to applying technology across our provider systems is understand that not every patient is the same. Some patients don't have the ability to go on to a website and schedule a visit. Some don't have the ability to go into a cell phone and go into an app and figure out how they're going to access the system. So there's different levels. We have different educational levels. We have different levels of capability across using electronic platforms, whether it's apps, the website, etc., and a well-organized system is able to accomplish meeting the goals of all of their patients, whether they are technology-enabled or not. Technology enabled. So we're seeing a lot of new technology in what's called the rev cycle space or really the billing and collection of services in the hospital system. And what we're seeing is technology now that allows the patient at the time of check-in to pay any outstanding balance they have. So it eliminates dealing with the front desk and being able to figure out what do I owe, when do I wait, how can I get service? We're also seeing tools that are allowing patients to go in and pay on an online basis. So not every tool is set up for every patient. As we talk about, there are different capabilities, but the provider systems are trying to figure out ways to get patients to pay in a more efficient manner. We're seeing things like member liability estimation that estimates, either prior to or at the point of service, what you're going to is out of pocket so you can start making plans to pay that. Because the health system is really the only system in our country that doesn't require full payment at the time you receive the good or service. You know, we all go in, we get a service at some point in the future. A bill shows up in the mail for our copayment, our coinsurance, our deductible, or whatever, and we're now trying to figure out ways in the health system to much more effectively tell a patient at the time of service or even when they schedule that service, here's what you're going to do out of pocket so here's how you need to be prepared to pay for it.

Dr. Jerome Pagani: So it sounds like that is the benefit benefit of some of the regulation around price transparency. Patients get the benefit of being able to see upfront, transparently what they're going to pay and health systems then sort of decrease the time between when they deliver the service and reimbursement.

Wally Ward: That's exactly right, Jerome. The big challenge we have in healthcare today is healthcare is really the only part of our economy where there's no price on anything. When you walk in to get a service, you don't know what you're going to pay and what you're going to owe. The only pricing in healthcare is in the pharmacy on those items in the pharmacy that are what we call across the counter. But the rest of the time is really, you know, I'm kind of guessing what I may owe. So the goal of price transparency is to make the healthcare consumer a better consumer of healthcare so that they can start price shopping, they can start comparing, what am I going to get at this provider for this price versus another provider at the other price? Now, the challenge with price transparency, it's not the end all. You still have to understand what's the quality, what are the outcomes you're going to get, because the most expensive healthcare is not always the best healthcare, and the least expensive healthcare is not always the worst healthcare. So there you have to be able to understand, what kind of outcome am I going to have for what I'm going to pay? But we need more price transparency if we hope to get the consumer to be a better consumer of healthcare.

Kevin Erdal: Yeah, and as you can hear throughout this particular use case, the timeliness of the data is incredible, right? It has to be in real-time and it has to be at the fingertips of some of the folks that are helping the patient that's in front of them. So that just goes back to some of the interoperability and some of the trust in the data that we've talked about today.

Wally Ward: And that's exactly right. The data has to be trusted. I, as an individual have to be able to trust the data. If I'm going to go into a provider's office and they're going to tell me you need to pay me X out of pocket today because we estimate this is what it's going to cost, and if I don't trust that data, I'm not going to be as willing to do that. So the trust in the data is key.

Dr. Jerome Pagani: Kevin, earlier you mentioned using the EHR for operational purposes. What kinds of data are we talking about?

Kevin Erdal: Yeah, so your operational data, you can think of provider efficiency or nurse efficiency or overall throughput for an example for a specific patient that maybe presents themselves through the ED that then needs to go in for inpatient stay and then have some recovery services, whatever the scenario may be. But throughout those kind of processes, we've also started to learn that we can start to leverage some of the ancillary data or some of the metadata that's associated to the documentation that's happening. Each EMR in today's world, or HER, is going to be implemented slightly differently at every location they're at. And we've been doing a lot in the industry over the last decade to try to reduce the variation. But the fact is, when we get into the nitty gritty details, each implementation is slightly different. So at that point we have to start to figure out, how can we leverage some of the metadata to start to integrate and then inform broadly beyond the in-EHR or in-application kind of reporting? So I mentioned earlier for cardiology within a specific department, we've gotten really good at looking at patients that have presented themselves to the cardiology department, look at some of the statistics around them related to what physician saw them, what nurse cared for them, what kind of medications are at- they’re on, excuse me. But now, when we start to expand that, we need to start to figure out, okay, what is the documentation that's happening after that patient left the organization, and how is that impacting the cardiologists, for example? How is it impacting some of our call centers or the way in which those patients are calling us back? We think a lot about readmission, for example, but we don't always think about how those patients are then interacting with clinicians, whether it be a nurse or a provider, while they're not in the hospital. So we can start to use some of that, I'm calling it ancillary data that's kind of post-visit or outside of the particular visit.

Dr. Jerome Pagani: And while your team must be thinking about how to use those data in a clinical front as well.

Wally Ward: Yes, absolutely. All of our clients are trying to figure out how to improve their clinical efficiency. As we talked earlier about the reduction in staffing that we've seen over the last few years, not voluntary but involuntary because of what might be referred to as the big quit or, you know, the big resignation. A lot of people in the healthcare system with the pandemic got burned out from dealing with the COVID and all of the patients and their issues and we've just seen a lot of people across the economy just choose not to go back to work for whatever reason. So we are having to leverage data to try to do things more efficient. So more of what we would call, you know, not, not necessarily doing more with less, but doing as much with less. So years ago when we talked about automation, there was a fear that it would put people out of work. Now the key to automation is helping to get the work done with less people. So we're seeing data being leveraged to, you know, direct virtual care, determine who the patients are that we can treat virtually versus having to see them in the office, being able to look at how we begin to solve inequities within the healthcare system, how do we get everybody with access to care, where are there access points, what are the services they need, how did they get there? For some people, transportation's an issue. For other people that may live in an area where there aren't all the services they need. So how do we start to provide those services in those different areas and leveraging that data to provide a barrier experience for the patient? And the real key to all of this data is being able to design clinical workflows so that we wind up with healthier people, both our own staff as well as our patient population, so everybody has a better experience in dealing with the healthcare system.

Dr. Jerome Pagani: That's fantastic. Wally, Kevin, thanks so much for joining us today.

Kevin Erdal: Always a pleasure.

Wally Ward: Thank you. We enjoyed it.

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