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December 3, 2021: Building analytics capabilities can clearly, directly and meaningfully impact success in value based contracts in an ACO (Accountable Care Organization). At Summit Health, they are able to give care with better outcomes at a lower cost than the market because of their knowledge of data and their multi-specialty outpatient structure. Joining us today is Dr. Jamie Reedy, Chief of Population Health and Dr. Ashish Parikh, Chief Quality Officer. What is the foundation for ACO analytics? Where does the data come from? What issues can arise with claims data? How do you address data quality? What areas do you prioritize first? How do you align incentives? How do you identify risk gaps? And what is the impact on annual wellness visits?

Key Points:

00:00:00 - Intro

00:09:20 - In this age of virtual care, telehealth and remote physiologic monitoring, data is critical for coordinated and comprehensive patient care

00:14:40 - It's often easier to define data quality by exploring what it feels like when it's absent. 

00:16:25 - Certain health plans will have selective inclusion or exclusion criteria. And this is unfortunate. 

00:24:20 - Pharmacy is one of the largest and fastest growing segments of healthcare expenditure

Summit Health


How to Use Analytics to Drive ROI in Value-Based Care with Summit Health

Episode 468: Transcript - December 3, 2021

This transcription is provided by artificial intelligence. We believe in technology but understand that even the smartest robots can sometimes get speech recognition wrong.

Bill Russell: [00:00:00] Today on This Week in Health IT.

Dr. Jamie Reedy: While there are many aspects of data quality that can and should be assessed, there's a few key signs that lead to confidence by end users in the quality of data. And we have really found those to be the correctness, the completeness, the integrity, the validity, and the relevance of the data. And addressing all of those are just, just incredibly important.

Bill Russell: Thanks for joining us on This Week in Health IT influence. My name is Bill Russell. I'm a [00:00:30] former CIO for a 16 hospital system and creator of This Week in health IT. A channel dedicated to keeping health it staff current and engaged.

Special thanks to our influence show sponsors Sirius Healthcare and Health Lyrics for choosing to invest in our mission to develop the next generation of health IT leaders.

Before we begin, I want to share an exciting announcement for This Week in Health IT. Starting in 2022, we're going to have four channels to bring our community more specialized content for your specific needs. The four channels are [00:01:00] News, Community, Conference and The Academy. The News channel we'll have our Today and Newsday shows where we explore the news that is going to impact health IT. The Community channel is just that. A place where we come together and collaborate. One of the distinctions of this channel is that we will have guest hosts from the industry and people that they invite to talk about the topics that we wrestle with every day. Things like clinical informatics, data security [00:01:30] and the like.

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Finally, this channel, the one you're listening to right now will become our Conference channel. [00:02:00] The same great content you travel across the country to receive. We're going to be bringing to you right on this channel. This show will become Keynote, where we do our long form 50 minute interviews with industry leaders.

And we will be augmenting that with Solution Showcases and briefing campaigns that introduce exciting solutions in more detail. For more information on our other channels and where you can subscribe visit us at this - S H O [00:02:30] W S. Now onto the show.

We have Dr. Jamie Reedy Chief of Population Health at Summit Health and Dr. Ashish Parikh who is also at Summit Health. And I'm looking forward to this because this was a presentation that you did at HIMSS. And I, I was fascinated by the analytics around the ACO, analytics around population health. So thank you very much for coming on the show.

Dr. Ashish Parikh: Thank you for having us.

Bill Russell: I want to start with the basics. Tell us a little bit about Summit Health [00:03:00] and the area you serve and the the work that you guys do.

Dr. Ashish Parikh: Sure. Let me kick that off Ashish Parikh. I'm the Chief Quality Officer for Summit Health and Summit Health grew out of the merger of Summit Medical Group, which is a multi-specialty. Over a hundred years old in Northern New Jersey, across the full spectrum of outpatient and ambulatory care. We have over 80 specialties and we offer comprehensive, coordinated care on a single EHR to all of our population. And in 2019, we merged with City [00:03:30] MD, which has 140 plus locations of urgent care centers across Metro New York, including Northern New Jersey. We thought it was a perfect merger in order to give that comprehensive continuum of care, whether it was from pediatrics to end of life, whether we think about it from prevention and primary care to chronic condition and kind of end stage management and from ambulatory office based to urgent care to, to hospital-based care.

That's what Summit Health ended up being. We do have a small group out in Bend, Oregon. [00:04:00] Summit Health also. Hundred plus providers with a similar structure.

Bill Russell: So Oregon, New Jersey and New York, that seems like a, not necessarily a geographic strategy. Seems like it's a strategy based on something else. Am I missing something there?

Dr. Ashish Parikh: Well, New York and New Jersey has been a geographic strategy and we were trying to expand concentrically from where we have our population density bend Oregon was just an opportunity to, to have a group join us that had a very similar philosophy and ability to care for their patients in a truly [00:04:30] coordinated fashion similar to what we do.

Bill Russell: So number of, of managed lives that the ACO covers?

Dr. Ashish Parikh: So we have about over 165,000 managed lives in both Medicare, Medicare Advantage, as well as commercial value-based contracts in New York and New Jersey. And then about 25,000 out in oregon.

Bill Russell: Fantastic. All right. So that, that gives us the scale. Tell us about the ACO vision and the journey that you've been on.

Dr. Ashish Parikh: Sure. So as I said, Summit Medical Group started as a [00:05:00] multi-specialty group. And what we found whenever we looked at data, whether it came from Medicare, from, from our peers is that we were able to give care with better outcomes at a lower cos thant our market because of our multi-specialty outpatient structure. And so about a decade ago, we went into value-based contract agreements with, we start a little bit backwards for many groups who start with Medicare. And we started with, with our commercial partners and we started to add value based agreements progressively each year, one by one.

[00:05:30] And by doing this, we were able to control the number of contracts we were in the amount of risk we were in and the number of patients that were under our ACO and progressively increase that it also gave us a chance to grow our group at the same time. So in parallel to increasing the number of contracts and the amount of risks we can do to grow the number of primary care physicians we had and the supporting specialty physicians, as well as the population health management infrastructure needed to manage those patients over the last thing.

Bill Russell: Let's talk about the information [00:06:00] infrastructure a little bit. What's the foundation of the ACO analytics?

Dr. Jamie Reedy: Sure. So I can take that one. So in order to be successful in an ACO or any value-based program, we've learned that you need to have access to lots of data and you need to make that data work for you.

As we set out to assess a couple of years ago, our analytics options and potential vendor partners we quickly learned that we needed to seek certain foundational capabilities. First, we needed to create an expansive dataset as our foundation, which [00:06:30] allowed for integration of many disparate data sets. As we took on all these new BBC contracts and new populations that Dr. Parikh referenced, we wanted to move beyond the limited clinical data that was in our EHR and incorporate medical and pharmacy claims data from our health plan partners, as well as clinical alerts of encounters that were incurring outside of our four walls by adding in ADT notifications. Secondly we wanted really our workflows in the clinics to be data driven.

So we [00:07:00] prioritized the use cases where we wanted data to drive workflows. For example, active management of patient attribution is critical for success and accountable care. And this includes knowing who your patients are, where they are, how sick they are and what services they need to achieve optimal outcomes.

So as we invested in FTEs to support coding and quality and overall patient management, we were focused on ensuring that those staff were using the data to drive their daily workflows in those [00:07:30] areas. And the third foundation was we really wanted our analytics teams to have direct access, to normalize sets, allowing them to calculate performance on all critical components of value-based care success.

And develop enhanced and predictive analytics that would grow in sophistication and impactability as our care teams were growing in their ability to use the data, to inform their workflows. And we also needed our analytics teams to generate scorecards from these data sets that our providers and care teams could [00:08:00] use to know that their workflows were making a difference in improving health outcomes.

So those are a few of the foundational capabilities that we felt were really needed, where we needed data to support.

Bill Russell: So that's I mean, that's fascinating. So you have foundational dataset, you have workflow support, and then you have enhanced analytics is the foundation. So, talk to me about where the data comes from. We heard some of it's coming from the EHR. Some of it's coming from claims. Are there other sources of the data?

Dr. Jamie Reedy: There are. Data can come from [00:08:30] many sources across the healthcare ecosystem. As we explored our foundational analytics needs and as we've become more sophisticated in our ability to use data, we've learned so much about the various available data sources and we continue to explore additional sources that we plan to integrate.

In the early days, we integrated all the common data sources, such as health plan eligibility and health plan claims data, the clinical EHR data and practice management data, data from our core facility partners. So hospital admission and discharges [00:09:00] and various reference files that were very unique to our value based care contracts. But there are other data sources that facilitate connectivity to an extended network of data. That's highly valuable for patient care. For instance, as we progress deeper into our risk journey, adding data related to risk adjustment, and coding gaps became critical. And in this age of virtual care, telehealth and remote physiologic monitoring data is critical for coordinated and [00:09:30] comprehensive patient care.

And now there are more and more sources of socio-demographic data as well that help us understand the potential social needs of our patients, which are incredibly important influencers of health outcomes. So that the data sources we integrate are really driven by our business needs and prioritized by considering technical challenges for accessing the data with each of these data sources.

There's just constant trade-offs between getting the most or the best data and leveraging what's easily available and easy to integrate, to match to our [00:10:00] current data sources. So we really can create that full clinical picture for each of our patients.

Bill Russell: On the show, we've talked about a whole patient profile, building a whole patient profile and it sounds like you guys are getting pretty, pretty close to that.

Can you touch on the social determinants data real quick. Where are we getting that? Are we getting that from surveys and that kind of thing? Are we actually connecting into I don't know, some partners who are bringing that data into us?

Dr. Jamie Reedy: Sure. So we've just begun our journey to figure out the best way to collect that data directly from our [00:10:30] patients. And we've started to do it through sort of preregistration processes and we'll eventually use our newly launched patient app to do some of that. We're also working on selecting a social needs vendor who will be able to help us with social needs referrals into the community and the whole closed loop referral process, which will include a full social needs assessment template that patients can complete.

But in the meantime, our analytics vendor has incorporated into their platform a census track data. And the [00:11:00] US census data that it's collected actually annually, I believe it's called the American community survey is integrated right into our platform. And so that data at the zip code level helps to inform some of the risk stratification of our patients within our analytics work.

Bill Russell: Talk a little bit about the value and the role of the claim.

Dr. Jamie Reedy: Absolutely. In our experience, obtaining medical and pharmacy claims data from all of our health plan partners has been really critical for mutual success, managing financial risk in an ACO or in any sort of incentive [00:11:30] arrangement requires insights about patients, patterns of care and utilization outside of our own organization.

And so complete claims data provide us that full visibility. In the early days of our value based care journey, our health plans were actually reluctant to provide this level of data, but we're finding now that most health plans are open to providing the data limited only by regulatory and privacy concerns.

When we first started working with our health plans to receive claims data, we found ourselves in a position of having to [00:12:00] explain and justify what we would do with the data to find actionable insights and then implement work. So for instance, we explained to them how we use pharmacy claims data to calculate our providers, generic prescribing rates at a therapeutic category level, and then hold the providers accountable in our incentive program to using cost-effective generic alternatives.

We also use claims data to assess where our patients receive care such as ambulatory procedures and infusions. And this data allows us [00:12:30] to better educate our physicians about the cost differentials between different sites of care and allows us to develop patient facing message about the value of outpatient non-hospital sites of care in order to avoid the claims data gaps, or lags and receipt.

We have developed standard data provision language that we include in our value-based care contracts that outlines our expectations upfront. And if the health plan does not provide the data that we need to manage risk, then there are consequences for the overall [00:13:00] contract reconciliation because this data is so incredibly important to mutual success.

Bill Russell: I'm looking at your presentation and you go into data quality and I'm going to ask the question, which sounds like I'm not a former CIO for a health system, but how important is data quality and which I think I know the answer to, but how do you know that your data is high quality and that it is trustworthy?

Dr. Jamie Reedy: Yeah, great question. Data quality is absolutely paramount to this work. As any organization builds out their analytics infrastructure, poor data quality can [00:13:30] completely derail your initiatives. And this can happen in many ways that that really justify baking data quality into the overall strategy for data integration from the very beginning of this.

Organizations should consider really two important consequences for data quality. If the care teams using the data find flaws, or don't have confidence in the data, they're going to disengage with your analytics. And then additionally, if your care teams need to confidently use the data for its intended purpose, if the data doesn't readily support that accuracy or [00:14:00] efficiency of use, they're going to further disengage.

So incredibly important to get it right from the beginning. We desired strong engagement with our data. We were hyper-focused on data-driven workflows. And so when we built out our analytics platform from the beginning, we built in strong data quality review processes. Every data set that, that we integrate is put through rigorous review and testing before it's incorporated into productionized analytics.

And while there are many aspects of data quality that can and should be assessed, there's a few [00:14:30] key signs that lead to confidence by end users in the quality of data. And we have really found those to be the correctness, the completeness, the integrity, the validity, and the relevance of the data. And addressing all of those are just, just incredibly important.

It's often easier to define data quality by exploring what it feels like when it's absent. And there are some emotions and responses that our physicians and their care teams would experience that reflect a potential mistrust of the data. Like really can be overcome by strong [00:15:00] data quality review processes.

So for instance, lack of confidence in our unreliability of the data, data that's new and unfamiliar may not be understood and hence not engender confidence in end users. Or uncertainty is common when clinicians are unfamiliar with a source or completeness of data. And so provider education about the data sources and how we validate them is, is absolutely critical to successful use of the data.

And then excessive variability in month over month reporting can cause [00:15:30] confusion and lead to difficulty, really gaining insight from the day. We recognize that variance is going to exist in any dataset, but minimizing this upfront through strong data quality processes is, is really absolutely critical.

Bill Russell: Now you're getting the claims data from trusted sources. But I noticed in your presentation, you talked about some of the issues with claims data. What are some of those issues?

Dr. Jamie Reedy: Yeah, I think there's a number of things that we can highlight. As we've mentioned, claims data is critical to managing financial risk and outcomes.

And really in [00:16:00] order to effectively use claims and organization has to have a full understanding of the very common data issues that are encountered with claims. So a few that come to the top for us. So due to privacy regulations, there will be data that's masked or hidden in the plans. Sensitive diagnoses or procedures will often be masked and you have to take that into account as it will result in gaps in knowledge about that longitudinal care that the patient is receiving potentially outside your organization or their utilization patterns. We've also [00:16:30] found that certain health plans will have selective inclusion or exclusion criteria. And this is unfortunate. We have a payer, for instance, who chooses to omit and DC codes and prescribing providers from the pharmacy claims files. Renders almost useless for our clinical pharmacy team. Health plans often change file formats, or they add or subtract data elements. And this can result in failure of automation delays in gaining access to the data.

So we work with our health plans to make sure that we're reviewing these changes in advance and as much as possible in [00:17:00] order for our vendor to be prepared. And then health plans often do not include indicators of whether a service is provided inside or outside of the health plans network. And given that out of network services are, are usually so much more costly and payers are often holding us accountable to in network referral rates, this can make it very difficult to measure performance.

Bill Russell: Is it easy to address the claims data quality issues?

Dr. Jamie Reedy: Well, keeping in mind these data nuances that I was just mentioning I would recommend that any [00:17:30] organizations develop a very proactive strategy for managing claims data quality and really this is relevant for non claims data sets from any external partners.

But, as part of our ongoing partnerships with our health plans, we educate them regularly about how we're using the data to guide better care for their members. And when the health plan understands the importance of the data to the care of their patients, There's so much better cooperation with us.

As I mentioned before, we build language into our contracts upfront that require timely and complete provision of [00:18:00] claims-based data feeds. We really try to require a health plans to provide timely notice of changes in the format or content so we can anticipate and prepare. And we agree in advance about how discrepancies will be handled.

When we do receive external files for integration, our vendor routinely assesses the files and notifies us of any lags or incomplete files. They're running inbound, telemetry and quality checks on all files before uploading them. And if a file does fail, we're able to quickly assess why. For example, where new data fields [00:18:30] added that we weren't notified of.

And then we go back to the health plan and we quickly, work through those issues. And then all of our files are reviewed with respect to EMPI mismatches, and other standard data quality checks, which really helps us discover very consequential changes well in advance before that data gets incorporated into downstream reporting that's used to inform workflows.

Bill Russell: As we know in technology projects, the data and the technology that that's a heavy lift but it's really only probably a quarter of the story because now you've got to, [00:19:00] you've got to get it in the clinician's hands. You've got to create value from it. So now that that foundations in place, which is really exceptional from the health systems I've talked to in the country, that is an exceptional program. And I really applaud what you guys have done. Let's talk about what we're doing now. So how will the ACO's drive value from that data?

Dr. Jamie Reedy: Sure. So as Summit thought about driving value out of our many integrated data sources to support patient care and to support our business decisions, we narrow down to [00:19:30]three main priority areas.

First we wanted our data to inform the daily workflows and to immediately impact patient outcomes as I, as I mentioned earlier. Secondly, we really desired to use our expanded data set to give our providers real-time visibility into their performance and opportunities to improve care in the short term, as this would then inform the incentive programs that we put in place for not just our physicians, but for care team members as well.

And then lastly, we're [00:20:00] investing very heavily in the resources and infrastructure needed for best of breed population, health management. And we want to assess the impact of our investments and create ROI analyses that inform our future strategic decision. About hiring program development, overall growth strategies, and so forth.

We recognize that this data infrastructure that we've created is just the foundation, but we really wanted to put the, the value into those three categories so that we could justify, analytics [00:20:30]requests. We did refine these three priorities upfront and it really helped to inform key questions that we asked ourselves internally, as we considered sort of the best technology and analytics strategy for summit.

I would stress here that, that kind of revisiting the value question is what helped us to make sure that we had the right expertise internally to use and understand all of the data sources. We had to ask ourselves tough questions about did our internal tech teams have the expertise and ability to turn our [00:21:00] data sources easily into actionable insights.

And this question really led to an assessment of whether we desired to build our own homegrown solution and build the team to manage and maintain the solution versus buying a technology solution that was really custom made for the use cases and priorities that I just mentioned and that we were trying to solve for.

And ultimately for us, we decided that the quickest path to driving value out of our data would come from partnering with an experienced vendor. And so we turned [00:21:30] our attention to creating a true partner. With a vendor we ultimately selected that would allow us to grow and learn together how best to use our data on those three priority areas to really drive the value for our ACO as well as the rest of our value-based care contracts.

And the breadth of actionable reporting that you can create out of this data initially can be overwhelming and so we really narrowed it down in the beginning to just four categories. Reports that we're going to immediately drive workflows. Reports that would inform our [00:22:00] stakeholders. Analytics that modeled the ROI so that we knew that we were making the right investment. And then data that directly impacted our strategic decisions on growth and program development and clinical workflow challenges.

And I know Dr. Parikh's prepared today with a number of examples to show you what we did with our data in those four priority areas.

Bill Russell: Yeah, and I'm looking forward to getting there, but I, if you don't answer the question, I'm going to get a bunch of emails, which is who did you use?

Dr. Jamie Reedy: We're really fortunate to have partnered with [00:22:30] Arcadia.

Bill Russell: Fantastic. Okay. That saved me a bunch of emails. And and I appreciate you for the detail that you gave us around the program. And so let's, let's get to. We have this in place. We have this platform in place but there's a lot of different areas we can start going after along that chain to create value. How do you identify the areas to prioritize first?

Dr. Ashish Parikh: So basically like Jamie said first thing that should drive your decisions is better outcomes. We wanted to figure out how can we use our analytics platform and our [00:23:00] data to improve patient outcomes? Because we know that if we improve patient outcomes, we'll do well in value-based contracting.

And as a independent medical group we also have found that, that the more we spend on a patient in the ambulatory setting and the less we spend on the inexpensive care settings, like hospitals and emergency rooms and post acute care facilities, the better the outcomes and lower the total cost of care.

So the first thing we focused on was places like or areas like sniffs and hospitalizations and how can we [00:23:30] reduce those, reducing utilization to more appropriate levels and minimizing hospitalizations and rehospitalizations? So, things like we, we developed a post-acute care dashboard that compared our post care facilities that, that our patients are being admitted to.

We looked at our transitional care management program to see how can we optimize that to minimize readmissions to it, back to the hospital. Then we moved over to other opportunities. And whenever we think of value and we try to convert all of our [00:24:00] stakeholders into value based believers, we always use the value formula, right.

Improve outcomes, which is basically better quality, better patient experience. Appropriately capture disease burden so you have the appropriate cost benchmarks and then reduce costs. But again, if you do that, the outcomes part, the costs will follow. So then we looked at where are our costs opportunities. For example, pharmacy, we know it's one of the largest and fastest growing segments of healthcare expenditure, particularly biologics, infusions, and especially pharmacy.

So we, we looked at where's the [00:24:30] highest utilization in terms of which drugs and how can we move those infusions out of expensive outpatient hospital facilities into ambulatory infusion centers. And then further going down into, into what's the appropriate dosing, who's the appropriate patient and things of that sense.

So we looked at pharmacy. And then we moved on to more ambulatory level types of analytics in terms of annual wellness visits and things like that.

Bill Russell: You talk about making believers, value-based believers. One of the ways to make value based believers is to align the incentives. So, talk about [00:25:00] aligning the incentives.

Dr. Ashish Parikh: Absolutely. And, and again, we always lead with our providers and our clinical teams in particular. We lead with the fact that what you're doing is better for your patients and better to get outcomes. But as you said, it never hurts to have your incentives aligned with that.

And so we do have something called the universal provider incentive program. We call it U PIP for short. And so every single specialty has a, the physicians have 20% of their compensation tied to value based outcomes, including quality measures, [00:25:30] patient experience enhance access, and then accurate disease burden capture.

And so we have this perfect every single specialty, whether you're a dermatologist or pediatrician or behavioral health specialist, but in particular for our primary care physicians, we wanted to really move that one step further and tie a panel-based outcomes and performance and its impact on our value based contracts.

And so with our vendor partner, who really helped us iterate on this, we came up with a [00:26:00]couple of bonus measures for our primary care physicians. One related to risk adjusted admissions per thousand. Because again, if you can not only take care of the patients that come to see regularly, but also don't forget the patient don't come and engage with them, bring them in, make sure their chronic conditions are met.

You're going to keep them healthy and out of the hospital. So one measure was the risk adjusted admission 1000 and the other was a quality impact score, which took some of our major quality measures that are pairs of holding us accountable to such as cancer screenings and immunization rates and chronic [00:26:30] condition management diabetes and heart disease.

And we took their panels and what we saw, what was the impact of their performance on each of these quality measures on our value-based contracts. So it, it took into account the size of their panel, as well as the difference in performance for their panel compared to the summits overall performance.

And so with these elegant measures, we were able to give primary care providers data that shows them how well they're doing on their panel, how it impacts our value based contracts and how then secondarilty it will impact [00:27:00] their incentives.

Bill Russell: So you guys are doing this across a single EMR, is that correct?

Dr. Ashish Parikh: Yep. Absolutely.

Bill Russell: Yeah. In Southern California, I was asked to do this across a hundred different EMRs and man, what you're describing is really elegant compared to what we were able to do, given the complexity of pulling, pulling all that in and then delivering it back into the workflow. But let's talk about that workflow a little bit.

So how do you identify the gaps? Either risk gaps, care gaps, place the information into the hands of the physicians when they [00:27:30] can impact it. And how do you measure, this is a big question, but how do you measure the effectiveness of that program?

Dr. Ashish Parikh: Your absolutely right, it's much easier to do this with a single EHR platform, which we're, fortunate to have and was, was the strategy from the beginning, right.

We really decided that the only way to have comprehensive coordinated care is for all of our providers and the care team to be speaking to each other on the same platform. I'll give you an example with our disease burden capture strategy and how we put it into workflow. We really didn't want to have physicians or care teams going [00:28:00] outside of the EHR to look at lists or find patients who have gaps and things of that sort.

So for our disease burden accuracy, we already knew the codes that were building our EHR. And we could always put a surface those for our providers to, to make sure that they're captured every year and consequently addressed. Right? These are clincial conditions that need to be addressed. If you have a bill from you have to address them.

And so with our Katie, what we were able to do was additionally surface chronic conditions that the patient may have, that we haven't captured on EHR because they [00:28:30] wer e treated by providers outside of our group or their suspect conditions that based on, on artificial intelligence algorithms, you can find the patients on four different diabetic meds.

There's a chance that they're diabetic even going code. So our, our coding compliance team is able to take this combined EHR and claims data, find additional conditions that the patient may have, and then surface them within the workflow of the EHR so that the clinician can then decide, yes, this is a true condition I haven't addressed yet.

Let me go ahead and address it. Or [00:29:00] nah this doesn't really make sense. The patient really doesn't have this and they can go and just dismiss it, but they do it directly within their note. They don't have to go anywhere else to do that. So that's just one example. We have that similar workflow for quality and other things.

Bill Russell: One of the areas in your presentation I found interesting was a skilled nursing facility performance. And you sought to improve that performance. Talk about the role of data in that process.

Dr. Ashish Parikh: Sure. So we, we joined the next generation ACO in 2016 and with that when [00:29:30] we looked at that data, particularly the Medicare data, we found that one of the greatest opportunities and greatest variability in cost of care, as well as outcomes was in skilled nursing facilities.

And with our patients going to, to over a hundred skilled nursing facilities across the state, and even outside of our state, we have many snowbirds from New Jersey and New York that will end up in Florida and Arizona and other places we really wanted to figure out how can we help positively impact that care and those outcomes.

And so we started with the facilities where we send our own hospitalists and post-acute care [00:30:00] specialists to manage those patients. What we looked at in those facilities is the volume of patients that are going there. The length of stay of those admissions, the cost of those admissions and the outcomes. For example, how often are they sent back to the hospital from the skilled nursing facilities. And to be able to do that and then adjust it for, for for the risk and DRGs we were able to then have head to head comparisons of all of our skilled nursing facilities. And that helped us in multiple ways. One, we could find the most efficient and. And effective partners that we [00:30:30]want to drive more of our patients to works. And then we could go to these skilled nursing facilities and sit down and have frank talks with them about their data, right?

And say look, here's your length of stay for the same DRG as our other partners. And how can we help you improve that so that we can get better outcomes for our patients. And so we were able to develop this, a skilled nursing facility dashboard and it's been so successful that our Katie has actually taken this and made a part of their product that is now available to all of their clients across the network.

Bill Russell: That's exceptional and with the bundled payments [00:31:00] and things that are coming down the pike, I would imagine some people who are listening to this would be interested in how that whole thing came together. As we try to manage the continuum of care outside of the four walls, if you will. Specialty pharmacy also is another area I find interesting in your presentation. How are you addressing the specialty pharmacy, the costs, the leakage, all those kinds of things?

Dr. Ashish Parikh: Again as I kind of previously mentioned, we basically looked at the drugs that we had the greatest utilization for and decided to target those. [00:31:30] And we figured out that there's a couple of things you can do there.

One is the site of care, right? So, the same infusion done in a hospital-based ambulatory facility is going to have a significant greater costs than an ambulatory infusion center. And then secondly, we have our own infusion center. So if we're able to identify those patients that are getting infusions outside, getting particularly in hospital-based facilities and move them to our facilities, one, you reduce a cost of care.

Second, you have better continuity of care and pay better experience. And then third is actually a revenue generator for us while [00:32:00] reducing costs, it's kind of a win win win on that side. And then we were able to then optimize infusions also so we found that that not everyone was getting the appropriate dose.

There was a lot of overdosing or wastage and so being able to then pull that data in, we were able to identify those opportunities, educate the providers to, to make sure we use the optimal drug as well as the optimal.

Bill Russell: Such a great presentation. I hope a lot of people got to see it at HIMSS, if not, it's here for, for as they say, podcasts are great, cause they're [00:32:30] evergreen. So they can watch on YouTube. They can pick up this this podcast on our network. But let's, talk about the wellness visits, which is so critical for the success of any program where you're managing risks. Talk about how you were able to impact that.

Dr. Ashish Parikh: Sure actually, any wellness visits the report was actually one of the examples of what Jamie talked about in terms of looking at the ROI of our strategy. So we had already implemented a pretty comprehensive annual wellness wellness visit strategy several years ago and had [00:33:00] gotten our annual wellness, it's up well over 75% of eligible population. What we wanted to see, are we getting our bang for the buck?

Is it just that people are doing AWVs or is it making an impact? And with our analytics platform, we were able to show that patients who got annual wellness visits had multiple benefits. One is the obvious ones, things like they had far better quality gap closure site or care gap closures in some measures up to 40% greater than people that didn't have any wellness visits.

And on average, about 15% improved quality gap [00:33:30] closures. In addition, we saw that they had better disease burden capture also, right? So they, more of their, we tie annual wellnesses with a chronic condition visits. So we don't just say, okay, we're not allowed to touch you and we'll do the AWV and move on. We would also try to address all their chronic conditions and this way you're able to capture the disease.

What we had unexpected benefits that we didn't notice that people who've got AWVs had more ambulatory spend within our group for other things. Right? So they got more preventative services within our group. They saw more of our [00:34:00] specialists. And because of that, again, we remedied we generate more revenue while reducing total cost of care. And then the last thing we found was that people got Annual Wellness Visits tended to be continued, to stay attributed to our value-based contract populations. So again, again, makes sense, but the additional benefits we were able to show, and because of this we were able to go to leadership and things like any wellness visits and other things where we show the ROI, we're able to justify the investments to continue these strategies or to expand on these strategies. The [00:34:30] benefit of having robust analytics.

Bill Russell: So I've, I've gotten into a habit of closing my podcast in a weird way. And that's letting you guys have the last word and say, you know what question didn't I ask? What's the close for this? The takeaway that people should have?

Dr. Jamie Reedy: I can take a stab at that Bill. So, I think great question. Building analytics capabilities can clearly meaningfully and directly impact success in value based contracts in an ACO. In this presentation that Dr. Parikh and I assembled, there were really four takeaways about [00:35:00]analytics, right?

Analytics can inform when and how an organization takes on upside and downside risk and provide data that's really critical to effective negotiations. So that's, that's one. Secondly, analytics has allowed us to maximize our organizational investments by identifying the very best opportunities to create new population health initiatives.

Third, it allowed us to measure the impact of our programs and investments on the clinical and financial outcomes that we were achieving on our current. And then as Dr. Parikh talked about, in order [00:35:30] to truly be successful in a value program, all incentives have to be aligned. And so impactful analytics has supported well aligned performance incentive programs, which have allowed us to build an organization of true value based care believers.

So, so none of that would've been possible without the analytics capabilities that we build. So I'll leave you with that.

Bill Russell: Fantastic. I want to thank you two for your time. I want to thank you for your work and your contribution to the industry. If people wanted more information, is there anywhere they could [00:36:00] go?

Dr. Jamie Reedy: They're welcome to contact us directly. I think we're both on LinkedIn with our cell phones and email addresses and we would be happy to talk to folks about this work and share a share of war stories with others.

Bill Russell: What a great discussion. If you know someone that might benefit from our channel, from these kinds of discussions, please forward them a note, perhaps your team, your staff. I know if I were a CIO today, I would have every one of my team members listening to this show. It's conference level value every week. They can subscribe on our website [00:36:30] or they can go wherever you listen to podcasts, Apple, Google, Overcast, which is what I use, Spotify, Stitcher. You name it. We're out there. They can find us. Go ahead. Subscribe today. Send a note to someone and have them subscribe as well. We want to thank our channel sponsors who are investing in our mission to develop the next generation of health IT leaders. Those are VMware, Hill-Rom, StarBridge Advisers, Aruba and McAfee. Thanks for listening. That's all for now.[00:37:00]


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