moderator: walt ellenberger iii november 14, 2017 … in healthcare consortium... · walt...

SAP SE/AUDIO NAM Moderator: Walt Ellenberger III

11-14-17/12:02 p.m. CT Confirmation # 423771480

HANA IN HEALTHCARE CONSORTUM UPDATE CALL

Moderator: Walt Ellenberger III November 14, 2017

12:02 p.m. CT

Operator: This is Conference # 423771480R

Walt Ellenberger III: Good morning and good afternoon, everybody, and welcome to the last in the year

HANA and Health Care Consortium Update Call.

My name is Walt Ellenberger; I have the pleasure of the running the North America health care

business development, strategic alliances, I have the pleasure of managing the EPIC partnership

and the great work that we're doing with HANA and Health Care Consortium. I'll help monitor the

call today.

This will typically be the format that you're used to where this session, everybody will be on mute.

You can hit "star 6" if you have question during the presentation. We will save time at the end for

Q&A, you can submit that online or as I said before, to come off of mute, all you have to do is hit

"star 6". The presentation will be made available in retrospect along with the audio recording and

a transcript of this call.

So, with that, I am going to turn it over to Dan Exley. Dan, are you there?



Dan Exley: Yes. Good morning. Good morning, everyone. Well, thank you for taking some timeout of

our day to spend a little bit of time with your analytics friends in the HANA and Health Care

Consortium. It's been a busy year for all of us. I know I'm looking at the watch saying, "Gosh, it's

mid-November already."

I know for our organization, it's been a lot of cycles spent getting ready for a next EPIC upgrade

and also building out our new data center where we'll finally have our target of ((inaudible)) data

center integration, HANA with dynamic tiering and then the hybrid Cloud based HANA big data

services for Vora and Hadoop that's coming live as we speak. So, more to report about the

findings from those exercises here in the coming months. Tracking very well and some really

exciting used cases to help us on a range of issues and ((inaudible)) cost effective. So, looking

forward to sharing more of that.

I do want to ask for a moment, and I know we had said that sort of the "star 6" to unmute I

believe, but if you're joining us for the first time as an organization or as a leader within the

consortium, if you wouldn't mind identifying yourself. I sure would appreciate it.

I'll just pause for a second here. Is there anybody who is joining this call series for the first time

today?

Sean Vlad (ph): This is Sean Vlad (ph) from EMS Memorial Health Care.

Dan Exley: Welcome. Great. Okay. Well, as we proceed through the call, if you have any questions,

feel free to speak up or submit them through the chat.

Are there any others of the leadership team for the consortium that have any updates to offer this

morning before we get to the main event from our partners at Mercy Health?



Walt Ellenberger III: And, Dan, I know that I'm not Mercy is on the phone but I know Parkland, Jon

McManus is having some long overdue vacation and he's getting married. So, that's ...

Dan Exley: I was going to say he has to get married to take a vacation.

Walt Ellenberger III: That's right. It was mandated by the real boss now. So ...

Dan Exley: Okay. All right.

Walt Ellenberger III: All good.

Dan Exley: Well, that offer -- then I'm going to turn the microphone over to J.D. Whitlock, vice president

of enterprise intelligence at Mercy Health, to introduce his team and walk us through their story

about improving performance in ambulator access at Mercy Health. So, J.D., the floor is all

yours.

J.D. Whitlock: Thanks, Dan. So, you saw our names and titles here a minute ago. So, I won't spend a

lot of time on that. We are going to talk about first major project on our HANA platform. I'm going

to give a little bit of background and hand it over to Karen Schwager (ph) who is our main

customer on the business-ness (ph). She's going to demo dashboard. And then at the end, we'll

talk about some geeky stuff for the platform.

So, a little bit -- I'm sorry. (Amick), I'm sorry. I was -- thanks. So, a little bit about Mercy Health.

We're the other Mercy Health, not the St. Louis Mercy Health, the Cincinnati Mercy Health. And

of course, the second Mercy Health in this consortium is the -- our St. Louis brothers and sisters

who are one of the leaders.



Similar to our brothers and sisters in St. Louis, large integrated delivery network, a lot of

employee providers, a lot of hospitals, a large single instance of EPIC. Although notably, only 50

percent of our hospitals -- or only 50 percent of the way through acute revenue cycle. Everything

else ((inaudible)) but only 50 percent of the way there, which actually, has something -- which is

actually relevant for the reason that we chose what we did for our first project here.

We have relatively decentralized analytics teams in BI tools. I'm not going to go through them all

right now. But that's also sort of relevant to our strategy here.

A couple of years ago at Hims, we saw what was going on with the HANA Consortium. We met

and talked to some of you and joined some of the consortium calls just like we -- similarly, we

have a few folks on today that might be just trying to decide if they're going to invest in HANA.

And we decided we wanted to join the cool kid's club. And so, we did. And so, we've got a

relatively small, in HANA terms, investment with three units. We've got ((inaudible)) for (Bob J.)

and that was largely due to this consortium.

So -- and I covered the last part already. Okay. So, a little bit about our enterprise scorecard,

affectionally referred to COPR, Clinical Operations Performance Report. So, we have 30 key

performance indicators and this is very much a top down exercise in that hour leadership working

with clinical and business representatives across our ministry, develops these key performance

indicators every year. Every year they change a little bit. And this is how we manage the

organization.

Most of these performance indicators have some type of self-service drilldown. Depending on the

KPI and the data source, those -- they do come in different formats and different BI tools. And

each KPI is assigned clinical and operational owners that are then responsible for their

performance on the KPI. All relevant to what we're about to show in the demo.



So, this gets reported out at system level and at our region levels and market levels, distributed

directly, like an e-mail from our chief clinical officer and chief operating officer to over 2,500

managers and physicians. And then really just distributed to everyone because there's also a link

that goes out to just the e-mail to everybody at Mercy with an e-mail account.

And then each KPI also has a dedicated SharePoint side where we encourage all these

managers that are responsible for the performance on the measures to collaborate and best

practices, ask questions and also have access to the drilldown (Alex).

This is a slightly ((inaudible)), not exactly what it looks like but closer to what it looks like, just

seeing to the sense of it without showing the real data. Each -- clicking on the title of each KPI

takes you to the dedicated SharePoint site for that KPI.

30 of total KPIs, as I mentioned, six of which are strategic initiatives, more on that in a minute.

And then there is an example of each KPI having a clinical and business lead, that's also per

region and you can click on those and get to their e-mail. This shows the SharePoint site for the

KPI we're going to talk about, primary care ambulatory access. And so, typical SharePoint

functionality discussion board and this is showing the measure itself, and I linked the drilldown

slide.

So, six of the 30 are strategic initiative KPIs. So, in the immortal words of George Orwell, "All

KPIs are equal but some KPIs are more equal than others." And these are more equal than

others because they are tied to bonuses. And what's a little bit unique about what Mercy has

done here is that for leaders that get bonuses, the bonuses are tied to these six KPIs no matter

what their job is. In other words, you don't have hospital KPI for the hospital leader and

ambulatory KPI for the ambulatory leader. We are all working together for these strategic

initiatives.



Because of that, not surprisingly, everyone is -- of course, everyone is interested in all three KPIs

but ((inaudible)) really interested in the performance on these six. And so, one of those is the

primary care ambulatory access.

And next slide, please. Here is what that measure is, it's a relatively complex measure because

measuring ambulatory access is a complex topic, it's not one thing, it's not just average third next

available appointment, although, that's an industry standard and everybody uses, it's a bigger

concept than that, right?

We care about restricted slots, we care about slots per hour, we care about office visits per hours,

we care about patient satisfaction and what patients perceive the access to care is at their

practice. And so, we set targets for all of those as you could see there. And then the goal for

each practice is to meet at least three of our five of these components and then go for each of our

markets the specific number of their practices, meaning three to five targets.

And you probably saying yourself, "Wow. That's a complicated KPI. Just one KPI." Yes, that's

one KPI and it's complicated but sometimes you got to be complicated in order to measure

something as complex as ambulatory access for our patients.

So, the next slide shows what this chart looks like on the COPR, on enterprise scorecard. So,

this is measuring. So, our target here of getting to the magic number there of 86 practices, which

as you can see we have made progress over the year.

And now, I'm going to turn it over to (Karen) who is going to demo this. And by the way, (Karen)

actually was the person chiefly responsible for developing this measure in the first place and did a

wonderful job with a spreadsheet trying to track all this in a spreadsheet. But at some point,

obviously, you ran out of things you're going to do on a spreadsheet and that's why we went this

way with our first kind of project.



So, over to you, (Karen).

Karen Schwager (ph): Thank you. Can you hear me? To make sure I turn the mute off.

J.D. Whitlock: Yes.

Dan Exley: Yes.

Karen Schwager (ph): Okay. Good. Thanks. Yes. I'm happy to not be doing that in the spreadsheet

anymore. So, thank you to your team. You and (Brian) really saved the day.

So, this is our access dashboard. When that measure came to be, you can imagine we got a lot

of questions on how we were going to give them the information, the practice managers, the

information they needed to figure out how they're going to change practices and operations and

processes to hit the target.

So, I worked with Brian Martin (ph). So, I have to say, I cannot take zero credit for how awesome

this tool is. He really took the ideas and put it -- and made it happen. So, thank you, (Brian).

So, we worked on this for months. And as -- we have a very good tool now that the practice

managers, the COOs and all the regions really use to drilldown to the day by providers. So, it's a

really great tool.

And feel free to interrupt me at any point, stop me and ask questions.

So, I'll start. This is the overview. This first graph here or table shows each of our regions. The

number of practices that are currently meeting the target and then the number of practices that



they need to achieve the target. So, you can see six of our seven are hitting it. Cincinnati is

getting very close. Below is just a different way to look at it and shows the percent variants. So,

you can see Cincinnati is 6 percent away from hitting it. (Lorraine) and Springfield are right on.

All of these over here are linked to other tabs to give a little bit more detail. So, I'll jump into

those. Current regional performance. This is a good one. If you hover each one, it kind of gives

you an idea what the average department score is overall. So, in Springfield, the majority of

theirs, if you average it together, they're hitting 3.5 out of the five measures. Kentucky is 3.3.

And let's look at Kentucky. So, the next ((inaudible)) based on how many they are hitting.

Kentucky is doing a really nice job. They've made a lot of progress. So four of theirs were hitting

it, four, and then three are hitting three. So, they only really have one practice that didn't hit it yet.

Scroll down. This table usually shows all the regions but I'll just filter it. So, it's -- in Kentucky,

there's a total of eight departments. Six of those departments are hitting the target for (some)

restricted, seven are hitting it ((inaudible)) per hour, et cetera, et cetera.

Let me go back to the homepage. I'm going to leave it filtered on Kentucky for the rest of this.

Regional trending, this is one that is very helpful for the practices in the regions because you can

change throughout the year and you may have six departments hitting and then all of a sudden,

one month you come out and you have four, you're going to ask the question, "Well, which

practices fell off, which one is added?" And that's what this graph does a nice job of.

So, here you can see Mercy Primacy Care was hitting it, was hitting it and then all of a sudden,

they dropped one of the measures. They are still hitting it but it's one of the practice ((inaudible))

wanted to know, "Hey, what measure did we lose here?" They can then go research this specific

department. So, you can see all are (crossed out) when they move every month.



That's the one that people use the most, I would say. And then this is just your trend. So, they

were hitting six in January and they've been seven every time.

The year-to-date performance here, this is showing that six of theirs -- they hit their six target and

then they are also at a surplus. They have an extra one heading. So, they're doing a nice job.

Below, this one also gives them an idea across the board of all the measures by department.

Okay. This department, their score is two, they are hitting two and the two are office visits per

hour, an average third next available. They are within 5 percent of hitting the slots per hour but

they're not hitting percent slots restricted in the ((inaudible)) access domain.

So, they can then scroll down and see that for all their practices. They can export this out into

Excel or a PDF, whatever they prefer, sit down and have conversations with the practice

managers, show them their actual performance and say, "Hey, here's what we need to do. We're

really struggling here on access, the patient's perception here. So, what can we do to make

patient satisfaction better in this practice?"

And then, I'm going to go to practice, that would be next. This is a -- this is probably one of my

favorites and I would say, the regions feel pretty strongly about this one as well because it's an

easy quick scorecard for them for all the measures to see how they're doing. So, they can print

this one, page her off again, hand it to her practice manager and have those tough conversations.

So, this one, they're hitting three of the five. It quickly tells you that Mercy Primacy Care, here's

the results on all the five measure. And then below, you can see all the trending.

So, they really actually increased their slot but they're still ((inaudible)) registration but they're still

under target, so that's fine. ((inaudible)) and the business per hour. You can see there, patient

satisfaction is pretty flat and they really dropped their average third slots per hour or slots -- yes.

Pretty normal here.



So, then this graph here shows you all of them and your variants for the target. So, visits per

hour 6 percent away from hitting the target and the access domain, the (Fiji cap) is 3.5 percent

away from hitting target.

And then, the other that used a ton is this provider. Level scorecard, very similar. They can pick

a specific provider, say they want to have a conversation with that person. And they can say,

"Okay." Well, it looks like a good one. She's hitting it. But they -- if she wasn't, they could say,

"Okay, (Dr. Abbot), you're not hitting one. Let's sit down and have a conversation about this." Or

in her case, they could sit here and say, "You're doing a really nice job on X, Y, Z. Keep up the

good work."

So, this isn't necessarily just the way for them to go find the problem children, a lot of practices

also use this as a way to encourage people and show them maybe at the beginning of the year

they weren't hitting it and now, look at your great progress. You're not hitting three of the five.

And this press gaining one, pop it out. This looks like the five measures that make up our access

component. So, the five questions and then the survey. And it shows them which ones they're

getting the most responses on and which ones are really driving that composites. So, you can

see for her, the majority of her responses, she gets a (top box) response on seeing her patients

within 15 minutes.

Appointment, she gets her routine care when needed. So, you can see the five breakout

questions and how many survey responses. This one is a good one for them to figure out how

they can change and improve patient satisfaction for this.

Then, we'll go back here. I'm not going to go through every single one of these measures

individually. And you'll get a good flavor here when I show you, let's see, slots per hour. So, the

top is just the year-to-date, how are they trending. So, ((inaudible)) year-to-date slots per hour for



the region. Their -- they have about 4.4 slots per hour. Everyone is really hitting the target

except for (Lima) as a region and (there was) in 5 percent. You can drilldown on this too. This

one below is the one I'm going to actually drilldown on.

So, I'm going to filter on (Lima). And you can see every single month, how they're doing. So,

they are hitting it, hitting it, not, hitting it. So, let's drilldown to the practice. Okay. They are

struggling. What's going on here? It looks like the -- so then, it pulls up these individual providers

in that practice and so -- okay. So, these are their thoughts per hour by day. I haven't got into

the day but I'm on -- so, (Dr. Nate) seems to be struggling a little bit. So, it looks by day.

So, now you can see -- I guess I picked the wrong one. For this ((inaudible)). I don't know, it just

happened. Sorry, guys. Screen is freezing. So, you can see by month their day. So, on the

16th of May, he had 3.7 slots per hour but then it looks like he probably left the organization or is

on some kind of leave of something, which is why we don't have data for him, would be my

guess.

And so, that is another issue that some of the practices we have to deal it throughout the year.

They may have physicians leave midway and then all of sudden, they don't have all these slots

anymore. They had them and then all of a sudden, they're gone because the provider left or

retired or went out on short-term disability. So, this kind of gives them a way to drilldown and see

how that's driving their scores, how that's driving the templates and the access for the patients

and how they can recruit new ones to get in there, to fill that capacity that they need now.

So, most of the individual measures go to that same sort of level in detail. So, we can -- I'll

percent self-restricted here, maybe take a better crack at it time. So, similar thing runs self-

restricted. I'm not going to look at November yet because that's still coming through. Looks like a

practice. And then, it looks like that.



So, again, they're pretty much constantly over the 20 percent target but we are also not as

concerned necessarily. You don't have to hit all five, you have to hit three of five. So, this group

may not be a problem, there may not be something for them to focus on necessarily. They are

already hitting three of five. Maybe this works for their templates. But then you also get to the

provider level and say, "Okay. Well, does she really need to have 70 percent of her slots

restricted? I don't know. Let's go have -- let's go talk to her and see if maybe there's a way that

we can improve processes for her, so she doesn't have to have so many restrictions."

So, if you just look at July for her, like every other day, she spikes up. So, that's just something

they could do to have a conversation whether -- see, if there's anything that the practices can do,

some previous processes to make sure that do you really need those slots restricted? Can we

help you get your template organized better in a way that works for you but it's also better for the

patients?" So, those are the types of questions we are able to answer with this tool. It really gets

down into the ((inaudible)) and the detail, which is what the practice managers really need to

make changes and drive performance. But you have the summaries here for leadership who

don't necessarily need all the details.

So, it's been a great tool. (Brian) and I are in the process now of doing this for next year as we

have changed that access composites. So, we're looking at five different measures this year or in

2018. So, we're working on adjusting and upgrading this again to reflect these new five

measures.

So, are there any questions? And (Brian), feel free, if you have anything to add. Hopefully, I

covered enough. But feel free to ask questions or ask me to drilldown another way.

Brian Martin (ph): That was great. Thank you.



J.D. Whitlock: I just want to -- thank you, (Karen). I want to make sure we do some Q&A here because if

we -- the next -- where we're going to go to next is (Brian) going through some infrastructure stuff

which many of you are going to be interested in but some of you may not be as interested in.

And so, if we have questions on the demo and the functionality here, let's stop and do that before

we go to the next slides.

And I think you have to do ...

Walt Ellenberger III: "Star 6." Yes.

J.D. Whitlock: ... "star 6.'

Walt Ellenberger III: Yes. "Star 6" or you can submit questions online.

Dan Exley: Well, I'll kick this off. This is Dan Exley. I'm curious, what's the size of the user based that

you have for this among the practice managers and maybe even beyond that? And any tips that

you might share from your experience in deploying out the Lumira web based access dashboards

to those folks that we might consider as we're deploying solutions with the same technology to

new audiences in our own organization?

Karen Schwager (ph): Yes. So, I'll differ the technical piece of that rollout to (Brian) and (Anton) -- or

(Brian) and J.D. Sorry, J.D. But as far as the end user deploying this out, they were so happy to

have something new that was (drilled on) instead of them filtering and screwing up formulas of

Excel and then seeing it's not working. So, they were very happy with it.

We did a couple of training sessions and showed them the functionality and how to work through

it. (Brian) helps put together frequently asked questions, documents so that if they had questions



or they were working through it, they could check that first and then if all -- so, they could always

call me and ask.

But the end user really, really like it. It was a big upgrade for them. And I think we probably have

about 50 users but, (Brian), correct me if I'm wrong, I know -- I just didn't ((inaudible)) and request

to him to add more people because everybody wants access to it now.

Dan Exley: That's great. Thank you.

Karen Schwager (ph): Yes.

Dan Exley: Any other questions from anybody on the line? I don't see any coming in on the chat. I think

it's great. It's so practical. And it really illuminates how you've been able to level up for those

practice management key members and others, I'm sure. A great story. Thank you for sharing.

Karen Schwager (ph): Yes. Thank you. Thank you for having me. And thank you, (Brian) and J.D.

((inaudible)) your team's work. I really appreciate it.

Brian Martin (ph): Thank you, (Karen). So, J.D., you mentioned earlier a little bit of the geek are here.

So, I will try and cover it at a high-level, some of the technical pieces behind the scenes that went

into the solution.

So, ((inaudible)) where you saw actually had 11 different HANA queries. A data says under the

covers that we're running and over 50, probably close to 60 visualizations. Some of those were

region practice provider level perspectives on the same metric but we had to sort of switch things

up to accommodate the grain or the way things shifted slightly as you drilled down. In total, we

ended up with 14 pages after that, Lumira documents.



And I will say, we had to work with ((inaudible)) on a couple of different things there because you

have to rollout -- I mean, that was really pushing the connectivity for the earlier versions of

Lumira. 1.3.1.8, so that runs well and fine. It behaves nicely and our performance is actually

pretty good.

And I think (Karen) was right, it's probably about 50 business users and there's a handful of IS

and technical users in the background as well. So -- slide.

At HANA level, J.D. said that we have ((inaudible)) of HANA. We're using Cisco appliances. So,

we have two appliances, one physical machine carved up into two VMs for dev and tests. That

was around (Red Hot 6.7) and our (prod) boxes are dedicated machine on (Red Hot 7.2). All

three environments are HANA 1 SPS 12, the 122 flavor.

From an ETL perspective, we are using ((inaudible)) data services 4.2. We did look at smart data

integration and just felt like data services is a little bit more mature and robust for what we needed

to do. And so, that's where we're at with detail right now. And so, we start with 1.3.1.4 at Lumira

and then we've moved up to 1.3.1.8, which I think is where we'll stop as we look forward to

Lumira 2 for the 2018 KPI.

In terms of data sources, ((inaudible)) forces are large data source and we've got 40 to 50 sort of

(through) mini tables and another 40 to 50 of those DC category tables. And then, as J.D.

mentioned, we're ((inaudible)) data, those are daily XML fees. I think we have two files a day and

then we've got a smattering of small flat ((inaudible)) or manually ((inaudible)) tables with master

data, some of the target data or some of the historical reference data that we needed to put in at

one time.

And all of that is in production. Beyond production, we're currently looking at five different call

center databases for our preservice center in dev, a new XLM fees from Contact Intelligence,



which is a recruiting software that we're using for physicians. And then we do get some data

feeds from the Legacy McKesson on the financial side. And we have the ability to tap into the

clinical data although we have not yet gone down that road.

Slide. So, briefly, in terms of the physical model, I've really tried to keep things pretty simply, just

a one-to-one reapplication, mapping each source into a single HANA schema and really

leveraging the power of HANA for that logical data modeling and using that on the fly. In memory

performance too, the chief ((inaudible)).

We are doing nightly ETL refreshers and data services and HANA are fast enough that most of

our small moderately large tables load fine in a full load. At the end, we're up to 10 to 15 million

rows, we can load in like 10 minutes. Once we get beyond that, it starts to feel like maybe it's

worth the extra building the overhead to do a delta load. And so, we are doing that with a

combination of clarity (super) server, CDC log in that we've turned on there, then we're scrapping

with data services and then to sort of ((inaudible)) those changes into HANA. And that's ...

J.D. Whitlock: (Brian), can I interrupt you there. See -- just to explain ...

Brian Martin (ph): Sure.

J.D. Whitlock: ... CDC. Change Data Capture for the daily incremental. Not everybody may know that.

Brian Martin (ph): Sure. Change Data Capture, that's a number of database (vendors) have. Microsoft

(Simple) Server offers the opportunity to sort of journal out the changes that you're making to the

table separately so that you can scrape those in one spot and probably get those through ETL

tool.



And so, that was an alternative to what I think some of the other consortium members are doing

in terms of that ((inaudible)) alter approach where they're piggybacking off of what EPIC does.

So, this saves us an ((inaudible)) joined and some complicated like logic pushing that information

down to (Simple Server) where we have to drink a bunch of stuff back and then do a comparison

in the ETL tool to write the changes to HANA.

This -- we're drinking direct changes, ((inaudible)) sort of couple of major transforms and a little of

FQL on the ETL side and just spitting this straight in HANA and it's working very well. But the

tradeoff is a little bit of extra log in space and some set up by your DVAs on the (Simple Server)

side, but that's been worthwhile for us.

We are doing -- beyond the simple light replication ((inaudible)) handful of materialized use and

drive columns not because HANA wasn't fast, because it was certainly fast compared to any

other database. But in a couple of cases, it will -- it wasn't 10 seconds fast, it wasn't 5 second

faster, that type of Lumira inner activity that we wanted, or maybe it was something that was --

you know, was fast, it was memory intensive. And so, we wanted to sort economize on the

amount of memory we're potentially using at one time.

Slide. Beyond the Cisco model, when we get to the logic on semantic layers. I've been a big of

sort of doing -- using whichever tool works best. And so, we're doing a Hibernization, sort of

traditional database FQL views and then the calculation view. So, I -- for me personally, I feel like

some of the very simple denormalization and at the other end of the spectrum, some of the more

complicated like analytical functions or recursive aggression things work better for me in FQL

code or in generate columns. But then that's towards the middle of the road stuff is where I really

like the calculation views for the gooey and we're using those in two layers.

So, we've got a foundational core layer that drinks everything up from the view and where I'm

applying any sort of standard business name or hierarchies that we would want to use in any



visualization and then a layer on of that, that's still in that best practice dedicated data provider

layer that we were instructed to use, where I'm using the counters, the parameters, specific

functions and filters that are tailored to whatever the case -- used case maybe. And that,

altogether, is ((inaudible)) a really good performance.

And so, finally, sort of looking ahead, I just want to say, ((inaudible)) we're looking at the 2018

active measures. And I think two of the five we're keeping, one we're changing and there are two

brand-new ones and we're trying to do those in Lumira 2. We're evaluating those designer and

design studio to see which is going to give us a better fit ((inaudible)) the sexiness and the

appeal, the visual appeal on the inner activity that we get with Lumira 2.

We're in the process of doing some OS upgrades and planning to move to HANA 2 and we're

waiting for HANA 2 and then take an interest in dynamic ((inaudible)) actually, invested in two

additional appliances and purchased a couple of units over dynamic cheering. And so, in the

next couple of three to four months we'll be going live with the dynamic cheering.

Our business objects environment is coming up, the 4.2, in dev and we'll hopefully be therein

production in the next few months and that will empower us to do ((inaudible)) directly against

HANA, which we're excited about because I think that may open us in self-service stores first.

And then, in terms of new projects beyond the access dashboard, I mentioned the call center

stuff, the physician recruitment, there is interest in doing some deeper dives in the My Chart

activation, potential turnaround. (Karen) and I have played with no-shows and I think we're going

to do more of that in some year. And then ((inaudible)) I would like to get into are some of the

platform advanced features that only HANA can do. It ((inaudible)) special ((inaudible)) possibly

in the graph database pictures.

That was all I had. Any questions for me or questions ((inaudible)) (Karen) and J.D. ((inaudible))?



Walt Ellenberger III: It looks like we have a couple of questions online.

J.D. Whitlock: Yes. I'll answer those. So, for the ((inaudible)) applications, so some of the used cases

are like a traditional business development, you know, for a large health system, you want to

know, you know, where shall we put our next practice and drivetime and then population and all

of that.

So, we are looking at how can we get value leveraging what we have without too much additional

money. So, on this consortium call, maybe it was three or four months ago, somebody did some

really cool, you know, spatial stuff.

Dan, was that Memorial or was that somebody else? I forget who did that.

Dan Exley: That was us. Yes. We ...

J.D. Whitlock: Yes.

Dan Exley: ... had leveraging a thin layer of the ((inaudible)) spatial analytics tools but pushing all --

storing all the data and pushing all the compute down into the HANA platform.

J.D. Whitlock: Yes. Yes. You guys are doing some really cool (stuff). So, I think the issue is -- I think

the goal is, how can we do some cool geospatial things that our business development and other

folks would like to see without spending a whole lot of money. You guys had, I think, a couple of

layers of add-ons. Actually, Dan, it might be nice to talk offline sometime about ...

Dan Exley: Yes. Give me a shout.



J.D. Whitlock: ... what you guys have to ...

Dan Exley: Yes. There's a lot that can be done, obviously, with spatial engine, the data types and the

health care ((inaudible)) maps native on platform too.

J.D. Whitlock: Yes.

Dan Exley: ((inaudible)) develop, manage ((inaudible)).

J.D. Whitlock: We also took a demo from -- I'm not sure how you say this, company's name, (Galigeo) or

(Galegeo), they've got some nice plugins to Lumira to do sort of on the fly geocoding, and that

was a nice demo. We're also going to take a demo from Visual BI that has a geospatial plug-in.

So, we're sort of exploring what that looks like. We've also had a few snags of things that you

would think you could do. (Brian), what the thing that you thought we would be able to do but

couldn't do?

Brian Martin (ph): I think in the current version Lumira, there are some limitations for the line HANA

connections in terms of how it consumes the geospatial data types of the columns. But that's

right, I think you have to -- I think somebody ((inaudible)) plug-ins kind of circumvent or open that

up for us and that's why we're exploring those.

And that's specifically for discovery, I think designer because it's got more flexibility and

((inaudible)) as well.

J.D. Whitlock: Yes. Yes. So, we're exploring all of that. Let's see. From ((inaudible)) leveraging

Caboodle. We are -- we're definitely doing Caboodle like a lot of people were struggling to get

failure out of Caboodle because you have to Caboodle because EPIC 2018 is coming and then



all their enhanced project telescope and everything they are doing, you're going to have to be

doing, you know, the sequel 16 version rather than version 15. We're on version 14 going to

version 15 where we can do the ((inaudible)) comp store embassies. And we're looking forward

to doing that.

We are not loading large amounts of Caboodle data into HANA just because we're got a relatively

limited HANA investment and we're a large organization. So, we can't just start dumping large

chunks of Caboodle in there. But I suppose we might if we come up with a good used case for

that.

Brian Martin (ph): And if I can add to that. Also, say on the -- both on the (Clarity) and the Caboodle

side, some of those views or the ((inaudible)) score tables or some of the physical materialization

that you do aren't necessarily required with (ours). So, I have tapped into some of the FQL logic

or taken a seat behind the covers to understand certain business concepts. But I can do them

with a raw (Clarity) tables virtually in HANA in some cases where we've needed them, some of

the concepts.

J.D. Whitlock: And, (Brian), you want to take those next few questions from (Annie)?

Brian Martin (ph): The tool for the (flat-out) transfers. So, that is the (SAP) data services. We're using it

to either drink pure ((inaudible)) like the, you know, CSBs or to go through an ((inaudible)) like in

the case of (Press Ganier), potentially, that's physician recruitment data pulling into schema there

and then letting that shred into the -- that's one of the situations where it obviously makes sense

to shred in advance and (pike) up a little at one time to get that data into nice relational format.

And then the team structure ...

J.D. Whitlock: (Brian), that's a team structure.



Brian Martin (ph): Just entire or ...

J.D. Whitlock: You are really one really smart guy. You're ((inaudible)) one, right?

Brian Martin (ph): Yes. There are a lot of colleagues internally, you know, from other teams that I've

certainly collaborated with and then a number of consultants and resources, yes. But I'm doing

the ETL, the modeling, the DPA stuff at this point, buying large ((inaudible)).

Walt Ellenberger III: (Annie's) typing another question. (Annie) is busy.

J.D. Whitlock: Busy good.

Walt Ellenberger III: Life cycle managements.

Brian Martin (ph): So, we are -- I mean, so the ETL also has its own like repository there and promotion

tools with the data services repository. And within HANA, we are using the life cycle manager to

promote model content from data to ((inaudible)). Because earlier I mentioned a little bit of a

hybrid approach into the calculation views and (datas) level views. So, some of the saying is it's

kind of a traditional change venture approach where I am actually manually running scripts across

the management, promote things. But where I can, I'm definitely using the life cycle manager tool

to pull things up.

And that does -- so, anything you build with the calculation views, you can roll back and you can

sort of get their later version if you need to. And I get -- obviously, being a small team, I don't

have the word, I'll step on it ((inaudible)) at this point ((inaudible)) outside.



J.D. Whitlock: By the way, I want to go back to that little question. Part of our strategy there is once we

get on the Cloud stream ((inaudible)) that's supposed to really ramp up the performance

according to what EPIC's telling us. And also, using their universe generator facility where you

can take a fact table and dump out universes that are supposed to perform well.

We hope to do self-service on top of that with some, you know, parameterized reports that, you

know, they might not be this HANA level performance but they'd be good enough for some self-

service explanatory -- I'm sorry, exploratory type things.

You know, the other question is that you get to your (Clarity) team, that your (Clarity) team does

not have time to do. You know, how many of this procedure X did Dr. Y do and ((inaudible)) Z.

Those kind of things, we want to rollout that, you know, we don't have to dump all of that in. We

don't need the sort of the higher end dashboard that you just saw demoed, you can't do that for

every self-service application. So, that's where we're trying to get the value out of the -- you

know, the rest of our -- the business objects stack on top a little.

But, certainly, there may be some used cases where we saw certain chunks of little data we need

that additional performance or additional, whatever, data modeling or ((inaudible)) that HANA

would be good for and we could (welter) down the future.

Dan Exley: And we have -- I know Jon McManus has virtualized a large chunk of Caboodle content and

Memorial Care, we're looking at how we can use the smart data access, smart data integration,

SDA, SDI features or HANA to just reveal virtual tables for certain aspects of Caboodle and we

have performance testing going on right now. And sort of to your same point, there where -- we

may even before we get to the people server 2016 features decide, you know, if we're already got

our customers coming in through the HANA front door or what is the performance look like for

certain used cases into your point. It may not be, you know, sub second, you know, single digit

second response time for these virtual models on top of very focused used cases.



But if it helps us provide time or top up license work for our development teams and enables list

making out amongst the masses, amongst, you know, all of our colleagues that are in operations

that make their own lists instead of only being able to come to IT to ask for lists. No, they don't

know the difference between 15 seconds from 3 seconds at some level. Of course, that threshold

can be met and there's a point at which we do notice that it's not acceptable.

But I think while -- that's something I'll bookmark here, which is as we look into the turn of the

year and coming on 2018, we may want to get three to four different examples of how people are

approaching integrating Caboodle and HANA in different ways. Highlighted three approaches

here in the last few minutes but there are more and kind of do some of the -- highlight some of the

benefits and tradeoffs that each of those -- because we all face that regardless, setting aside this

((inaudible)), you got to have it. You know, ((inaudible)) EPIC and into the future.

J.D. Whitlock: Yes. Thanks, Dan. Yes. Great comments. I love to chat more about that sometime.

Another question from (Annie). (Brian), can you -- I know you're not necessarily expert on that

EPIC (SU) cycles but ...

Brian Martin (ph): Yes. I'll be honest, we've been -- I guess about a year now ((inaudible)) strong. So,

we've only been through one upgrade here and I guess we do bimonthly a few cycles. The one

upgrade is that was actually -- it was a manual glance on my part through the documentation of

the (Clarity) team to sort of look and see were there any tables or columns that were significantly

impacted.

I know there's a lot of metadata in the ETL tool and I know there are other tools within our

((inaudible)) that could do some of that lineage and impact analysis but I have not yet tapped into

those, to be honest.



J.D. Whitlock: Walt, I think, you wanted 15 minutes at the end?

Walt Ellenberger III: Yes. No, I ...

J.D. Whitlock: Or are we doing Q&A until the end?

Walt Ellenberger III: Yes. Well, you know, if there's any other Q&A we'll probably have, you know, time

for one more and then, Dan, I don't know if you have any closing comments. I can end up with

kind of looking ahead of what we have coming up, you know, wrapping up in the New Year and

earn that current year and then looking ahead in the near future.

Dan Exley: It looks like -- I don't see any other new questions coming in. I'll just share that we continue

to tease about this HANA (Fan), (HAKA Fan), (Co Jim), (New Jam), whatever you want to call it,

there's some -- particulars of what it can and can't be called, there were still learning from the

marketing wizards at SAP.

But we are still moving forward with providing virtualized environment and reasonable sized

dummy data sets for an event to really demonstrate for ourselves as in small teams, in the spirit

of what you see in (HAKA Fan). How we can quickly spin up some of the advanced features of

the HANA platform that we have access to, if you got it, or to the extent that anybody can get

HANA Express and download that ((inaudible)) now on the SAP website.

((inaudible)) for production use up to 32 gigs and modest beyond that, certainly for development

environments or very small applications -- well, the modest applications honestly, more of your

time. But we're -- we'll be looking at how we can build some of those hybrid solutions and we're

working with folks at SAP and some of the consortium leadership organizations to define exactly

how that will come about. But we're looking at things like IOT, streaming data integration from



sensors, quickly spinning up web apps, that would be consumer facing that integrate some of that

data with spatial and mobile.

So, some exciting used cases coming together there. And again, things that we all have access

to or could quick easily and how that add another level of transformation onto this ((inaudible))

that we can bring to our organization. So, more to come on that. As soon as we have a final,

final schedule date for that, we'll share that with all of you and ((inaudible)) every team participant

in that event with us.

And, Walt, I think that's about it. I'll turn it over to you to highlight the remainder of the schedule

as we know it.

Walt Ellenberger III: Yes. No. Appreciate that, Dan. And certainly appreciate, (Brian), J.D., (Karen), for

the work you've done and kind of the momentum you have created, that you are kind of the next

generation of the pioneers and the consortium. So, it's nice to see some new faces and some

new names and you know, some pretty cool used cases that, you know, you can share with the

group. So, thank you. Thank you very much.

Just like Dan said, we're going to -- there's only one more session we're trying to cram into a very

busy year already that's education oriented and it's going to be on December 7th and it's going to

be featuring the SAP Leonardo Enterprise Platform, digital platform, which is really an extension

of the investment that a lot of you guys have you already made in HANA and integrating IOT, AI,

block chain, you know, those component parts in an emerging world of, you know, devices and

data and making sense of it. And health care certainly opens up a lot of doors.

So, this session is more level setting what Leonardo is and the approach and cultivating around

the platform in health care. So, that's December 7th. And then, we're going to take a break,

we're going to kickoff of the year, as Dan said, with a new approach, you know, more of a working



session environment ((inaudible)) type of role. We're going to do a couple of these in the New

Year. We're going to try to squeeze this in between planning mania that's typical in January and

some of the bigger industry events. I March, you know, specifically Hims.

And then, we're moving out the more traditional regional showcase with Parkland, that's going to

after Hims, probably the end -- middle to end of March in Dallas, Texas with a lot of great used

cases in action with, you know, guest speakers. And I'm hoping to have those two invites bait

and we'll start the promotion work in the December time frame.

And then, we'll probably sneak in a large -- maybe an hour-and-a-half kickoff session to the New

Year led by Dan -- or Dan and the executive leadership team to the consortium, doing a recap of

what was accomplished and a look forward ahead in terms of, you know, topics, seminars,

approaches, investments that we want to make as a group, and that certainly will be an

((inaudible)) meeting for everybody to attend.

So, with that, we're pretty much coming up to the top of the hour. ((inaudible)) a couple of other

little questions that I can't see at the moment. But ...

Dan Exley: So, (Bill) commented that SAP's planning and (HAKA Fan) is ((inaudible)) development

summit in March health care used cases are welcome.

Walt Ellenberger III: Oh, perfect. That's -- yes. That's a great, great point. Thanks, (Bill). And we can

incorporate that into the, you know, normal communication chain. So, all good there.

And if there are no other questions, you know, Dan, certainly appreciate your time and leadership

as always and then Mercy Health team. And you know, we'll do a recap. J.D. and team were

kind enough to share the presentation. We'll made sure you have contact information and we'll

send all that out, you know, post gain.



And you know, that's it. We'll give you a couple of minutes back in the day.

Dan Exley: Thank you all and thank you to the team from Mercy Health, really appreciate it. Great work.

Take care, everybody.

J.D. Whitlock: Thank you.

END

moderator: walt ellenberger iii november 14, 2017 … in healthcare consortium... · walt...

Documents