July 16, 2025 • 22 mins
In this episode of the MGMA Business Solutions Podcast, host Daniel Williams sits down with Phill Tornroth, Vice President of Engineering at Elation Health. Together, they explore the revolutionary impact of AI on primary care, discussing how technology can reduce clinician burden, streamline workflows and bring human-centered design to healthcare technology. Elation Health received two awards from the 2025 Best in KLAS: Software and Services report: one for Small Practice Ambulatory EMR/PM and another for EMR-Centric Virtual Care Platforms.
Key Takeaways:
- 05:46 Clinical-First Strategy
- 09:15 Note Assist Innovation
- 11:37 Actions Feature
- 14:19 User-Friendly AI Design
- 16:41 AI's Potential in Healthcare
- 20:39 Validated User Experience
Resources:
- Visit the Elation Health website to learn more
- Learn more about Elation Note Assist
- Learn more about Elation Actions
- 2025 Best in KLAS: Software and Services report
- Connect with Phill Tornroth on LinkedIn
Additional Resources:
Email us at dwilliams@mgma.com if you would like to appear on an episode. If you have a question about your practice that you would like us to answer, send an email to advisor@mgma.com. Don't forget to subscribe to our network wherever you get your podcasts.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Daniel Williams (00:02):
Well, hi, everyone, and welcome to the
MGMA Business Solutions Podcast.I'm your host, Daniel Williams.
I'm a senior editor at MGMA andpretty much the host of the MGMA
Podcast Network. So you've seenme on here before. Today, we are
really excited.
We have a new guest here, PhilTornroth. He is a vice president
(00:23):
of engineering at AlationHealth. Phil's been innovating
in healthcare technology forover two decades and helping
build tools that reduceclinician burden and bring human
centered design to theforefront. What we're going do
is get to know Phil a little bitbetter, get to know a little bit
better about Alation Health, butalso something that's exciting
(00:46):
and on the top of mind for a lotof people, getting to understand
what is going on with AIdevelopments out there and how
they can support primary careclinicians. With all of that
said, Phil, welcome.
Phill Tornroth (01:01):
Thank you, Daniel. Happy to be here.
Daniel Williams (01:02):
Yeah, so good to have you here. We have a
connection. You're in the SanDiego area. I've got a daughter
in college down in that area, soit's really good. Maybe I'll
swing by and say hey to yousometime.
I never need an excuse to go outto San Diego. I love it there.
Phill Tornroth (01:18):
Yeah. Me too. Weather's great here right now
too.
Daniel Williams (01:20):
Yeah. So let's start out, Phil, just getting to
know a little bit about yourbackground. I I shared some
information, but what are somethings that you might wanna
highlight for our audience sothey could just get to know who
you are?
Phill Tornroth (01:34):
I've made a career in health care startups.
Those that those are basicallythe two through lines for for my
career mostly is almostexclusively in healthcare and
almost exclusively at relativelyearly stage venture startups. I
did the sort of first half ishof my career, specifically
focused on patient safety andpreventing medication errors in
(01:56):
hospitals. And I think that gaveme like a good sense of why I
wanted to work in healthcare.And I'm really grateful to have
had such a mission driven start.
I think maybe if I had startedin like hospital billing or
something, I could have run forthe hills. And then for the last
fifteen years, I've been focusedmostly on independent primary
care with Alation.
Daniel Williams (02:16):
Okay. I have to ask you. We're gonna get more
into AI, but is anything goingon in AI surprise you? Or do
were you enough into that fieldwhere you went, this is the
direction it's going? Did youhave any inkling?
Phill Tornroth (02:31):
No. It surprised me. The the truth is I so my my
real AI awakening in terms ofwhat we're gonna be able to do
practically in the relativelyimmediate term, I think, came,
like mid twenty twenty three.
Daniel Williams (02:46):
Okay.
Phill Tornroth (02:47):
And before then, I you know, I was paying some
attention to machine learning,but I didn't see us rounding the
corner as fast as we have. Andin truth, I've always been like
a little bit of a of a Ludditewhen it comes to new technology.
I like to see it work before,you know, I get too excited
about it.
Daniel Williams (03:08):
Yeah. That is so cool to hear from someone who
has a technology background thatyou're not just right there at
the forefront with everything,every new gadget and, iteration
that comes out. So that is I'mnot the only one. Let's learn
more about Alation Health. Iknow that you guys are a partner
of MGMA, and we're great to soglad to have y'all on board with
(03:31):
us.
But what I'm seeing here is thatAlation Health supports over
36,000 clinicians and is knownas the largest community of
primary care innovators. Tell usa little bit about Alation
Health. What do our listenersneed to know? Our listeners are
those medical practice leadersand decision makers.
Phill Tornroth (03:51):
Well, first of all, founding story is pretty
powerful and had a lot to dowith me joining. So Kina and
Conan were our founders. Andthey have a father who's a
practicing primary carephysician who just retired from
his practice but worked for manyyears in Walnut Creek. This was
(04:11):
around the time that likeMeaningful Use was showing up
and there was an enormous amountof incentivizing providers to
get off of paper and onto theseEHR systems. And they helped
their dad survey the field ofwhat was available and came to
the conclusion that thesesystems were going to be really,
frankly, existentially terriblefor these, especially these
(04:34):
small primary care physicianslike their father who provided
really complex proactive care toa panel of 1,200, 1,300
patients.
And the company was founded onthe belief that primary care is
our biggest lever againstdownstream illness and costs,
(04:57):
and that it's frankly, likeundervalued as an opportunity.
And that attention would turn inthat direction and that
technology was not on track tohelp provide leverage. So we
started Alation to focus veryspecifically on that.
Daniel Williams (05:13):
Okay. Give us an idea then. What time frame
are we talking about? When wasthat?
Phill Tornroth (05:18):
I think they started working on it 02/2009,
and then I joined as the firstengineer in 2010.
Daniel Williams (05:24):
Okay. All right. I wanted to follow-up
then about that work withprimary care. So how does this
community of Alation Healthsupporters, supporting over
36,000 clinicians, how does thiscommunity influence your
approach to integrating AI toolslike Note Assist into your EHR
(05:45):
platform?
Phill Tornroth (05:46):
Yeah. I mean, it was one of the things that we
would talk about a lot is havinga clinical first strategy.
Daniel Williams (05:52):
Okay.
Phill Tornroth (05:53):
So to like sort of double click into what I was
just saying, I think when KeenanConan looked at why technology
wasn't providing as muchleverage to clinicians as it
ought to, and as it did inplenty of other verticals where
technology was really reshapingworkflows, one of the things
that they noticed is thatvirtually all EHR companies are
(06:15):
billing companies at heart, andthen maybe eventually get around
to building an EHR or buying anEHR, but their focus is really
on billing. And we decided firstand foremost to take a clinical
first approach and focus firston what do providers need in
order to make this reallypowerful diagnostic tool,
because that's what the chart iswork for them. And how can we
(06:38):
add leverage? And when it comesto AI, a lot of our thinking is
centered in that same placewhere the first place we go is
what clinical workflows looklike, and in what ways could
this technology reshape andenhance those. And sometimes
that also means investing inbilling.
(06:58):
We have a billing platform andan all in one solution today,
but it mostly centers us andwhat do providers start the
practice to do? And how can wemake that as joyful and
efficient as possible? And howcan we make as much of the other
stuff go away?
Daniel Williams (07:13):
Okay, thanks so much for that Phil. Now, in
reading about Alation, the EHRplatform is known for its
intuitive design and the waythat has unified work flows. So
when we think about it that way,how are you designing the
products? How are you designingthings that can be implemented
for those medical practiceadministrators and other people
(07:36):
in healthcare?
Phill Tornroth (07:38):
Yeah, when we talk about unified workflows, a
big observation we have when welook at systems and features
that are failing in healthcareis that they often feel
compartmentalized. I think insome cases, the teams working on
these might shift their orgchart a little bit. So, you
know, really one of the keyinnovations in Elation early on
(07:59):
was just making it possible tosee disparate pieces of data at
the same time to be able to lookat a patient's medication
history next to your last visitnote or review historical
records while referencing yourown. So when we talk about
unified workflows, a lot of itis thinking about what the
purpose of this is first, andthen designing surfaces that
(08:20):
support that clinical workflow.We made the decision last year
to really lean in on AInatively.
And so by that, I mean, we hireand train and build these skills
in house versus dependingentirely on partners to build
solutions on top of our system.And one of the reasons is that
(08:41):
we really firmly believe wewon't be able to accomplish
those unified workflows in areally graceful way and
incorporate AI the way it shouldbe incorporated without doing
that. If we depend entirely onpartners, we're going to get
little pieces of the puzzle thatdon't really connect to each
other.
Daniel Williams (08:57):
Right. I noticed that earlier I I
mentioned the term note assist,and I didn't get you to
elaborate or define that. And sowe're just talking about it like
everybody listening. Oh, yes. Ofcourse, Noticist.
What is Noticist first? And thenI have a follow-up for one of
your new innovations in thatprogram.
Phill Tornroth (09:15):
Yeah. So Noticist was our our flagship AI
product that we launched lastyear. It's a natively built AI
scribe integrated directly Andinto so that means that it
records and transcribes yourconversation with the patient.
And in real time, every fewminutes or so, it transforms
(09:38):
that into note content. Itrespects your visit note
templates, and it'll fill themout for you.
It respects the problem listsand incorporates context that's
already in your chart. So itbecause it's natively in the
application, it has all thatcontext and you're not cutting
and pasting and assembling thisinformation from another tool.
Daniel Williams (09:57):
Okay, that is so helpful. So my follow-up is a
note I had from you is one ofyour latest innovations is
something called Actions. I feellike I'm talking to, you know,
somebody from Apple or somethinghere. It's all these really cool
iterations and new products. I'mjust I'm so excited about it.
I love this stuff. What isactions? What is that?
Phill Tornroth (10:20):
Yeah. Actions was a logical next big step for
us. Know, one of the greatthings about Noticist is that
you can focus on your patient.And we have a lot of doctors
that tell us like, this isamazing. I don't have to keep
jotting things down and usingthis half of my brain to reshape
information.
I can stay focused on mypatient. But one of the things
(10:42):
that we still saw providersdoing is needing to either like
review their note and make surethat they caught every to do
item that they needed to followthrough on, or some of our
providers would actually likehave gone back to a piece of
paper and we're keeping like achecklist in front of them. And
so what actions does is itlistens to all of the things
(11:02):
that you intend to need tofollow-up on in that visit. So
if you talked about refilling aprescription or changing a
dosage or sending a lab order,and also the things that might
not be as top of mind, like ifearly in the visit, you'd
mentioned that you were going toget the patient like a handout
on a certain set of exercises orwhatever. So we keep all of that
in the to do list.
And at the end of your visit,you've got it there. If you take
(11:26):
actions in the application, sofor instance, if you go to our
EHR and you write thatprescription, we notice that you
write it and we check it off foryou. And so it's this live list
of the things that you intendedto follow-up on.
Daniel Williams (11:38):
Okay. This may be a simplistic question, but I
I need to ask it for myself andhopefully for some of our
listeners here. When I work withAI and prompt and do that those
sorts of things, sometimes I'mnot getting the results I want.
So then but I know what I'mlooking for. So I go, no.
(11:58):
That's not exactly what I'mlooking for. Let's shift it
here, here, and here. Now you'redescribing when y'all are
building out your program, yourAI, you're doing that natively.
So how do you ensure that it'sgathering the information that
you need? That's something thaty'all are building into it on
the front end, or is itsomething where someone comes
(12:20):
back like a medical assistant orsomeone just to make sure that's
all being integrated, all thosenotes are being done the right
way?
Phill Tornroth (12:28):
Yeah, so our tools right now, the ones that
we've shipped are prettyagentic. So the AI listens,
records, remembers what you do.In terms of making sure that's
accurate, I think there's twobig levers that we talk about
and use as a team. One is we doquite a bit of pre formal
(12:48):
evaluation. So we build corpusesof data and we run through
enormous numbers of test casesand we're constantly iterating
and trying as new models comeout and things.
That's really important to us.And it's actually most of the
time and effort that our AIteams spend on these features is
writing and running those evals.The other lever that we use is
(13:10):
design. So building with AI isreally like designing for
failure and iteration and howcan we make like one of the sort
of jokes that's become a mantraon the team is this there's this
Mitch Hedberg joke about howescalators don't break, they
just become stairs. And so wetalk about that a lot on the
team is like, how can we designan experience where we make
(13:34):
failure safer?
Because these tools are gonnaget it wrong sometimes. And so
can we design a surface and anexperience that allows the
provider to still be in control,see what happened, recover from
these situations?
Daniel Williams (13:47):
Okay. Love that. Thank you for clarifying
that. So let's move to the nextstep here. Technology, as we
know, can help so much withworkflows, but can also if
somebody's not tech savvy, someof our healthcare professionals
aren't just up on the latest,greatest technology that's out
(14:07):
there available to them, wedon't want to disrupt workflow.
So how do y'all integratethings? How do you design it so
that it doesn't actually impedethe efficiency in the practice?
Phill Tornroth (14:19):
Yeah, absolutely. Mean, we do think
about that quite a bit andmaking sure that these
experiences have, like we'lltalk sometimes about these
experiences having off ramps oron ramps and like our, since
we're all learning how thistechnology is going be
integrated into our lives, andthere's such a variance in
fluency, we think a lot aboutmaking sure that these are
(14:42):
experiences that you can dip inand out of or that we have ways
for you to learn about themsafely. Yeah, also, you know,
the point about tech savviness,like I mentioned, I'm kind of a
bit of a Luddite and come lateto these things. One of the
things that I found so inspiringabout AI specifically is that
that adoption curve is kind ofreversed. Really early on when
(15:04):
we started working on Notisyswith some of our customers, I
talked to a couple customers whoran clinical teams, and they
were finding that the biggestadopters of these tools, the
people who latched onto them thefastest were the ones that had
the hardest time using acomputer.
Daniel Williams (15:22):
Wow.
Phill Tornroth (15:22):
Makes sense. These are providers that have
been on paper their whole life.And now the idea that they can
talk to their patient as opposedto having to click and type
through this note, It was just amuch more human experience for
them. So I've continued to seethat even on our own teams, and
I love that about thistechnology in particular.
Daniel Williams (15:43):
Yeah. And that that leads into the next
question I have for you. I havea note down here that you
describe yourself as a reluctanttechnologist and really with
your focus on human centereddesign. So let's talk about
that, you being a reluctanttechnologist, and then how that
goes into the products that youbuild out.
Phill Tornroth (16:04):
Yeah. What it means is I I've never really
been enamored by technology fortechnology's sake. I've always
been much more of a product anddesign person who happens to do
software engineering as a trade.And so don't worry, I hire and
employ lots of people who arefascinated with technology and
(16:24):
they're the ones that push me tolook at things and adopt. I'm
mostly the the the sort of like,person that, like, puts the
brakes on and asks, like, can weshow value with this yet?
Like, is this is this gonna makea real impact on real people and
push us to experience that?
Daniel Williams (16:41):
Yeah. I've got a couple more questions for you
before we sign off. So as we allknow, I have conversations
almost daily with peers, witheverybody I interact with. I had
this conversation recently withsomeone. I've only had a
smartphone for about fourteenyears, but I'm not young, and I
don't remember life beforehaving a smartphone.
(17:03):
I was telling you offline that Iwas just in Spain, and so I
didn't have a a SIM card. Iwasn't connected, you know,
where I was. So I actually had adetox of the smartphone, the
device, everything because Iwasn't staring at it every five
seconds. You know? I've adoptedback.
I'm back to staring at it. Butwhat I wanted to get to was with
(17:25):
AI, as you were saying, youradoption was around '22, '23 of
you know, just a few years ago.And we're already like, well,
what would I do without AI infront of me? And it is evolving
so rapidly. Where do you see itgoing, you know, in just the
near future?
Where are you looking around thecorner? What's your team doing
(17:46):
as far as where you think it canreally make seismic shifts in
health care in a good way?
Phill Tornroth (17:54):
Right. It has been so fast. And there's so
much opportunity that Isympathize. Like, I think a lot
of us just sort of want to,like, hit pause and breathe and
try to figure this out together.It's super exciting.
And it's super exhausting all atonce. One of the things that
we've been looking for isespecially now that we have, you
(18:18):
know, we went through thisprocess of building an AI team
at Alation, which I think a lotof companies did and build their
expertise in one team and thatteam built and shipped note
assist and shipped actions. Andthen really over the last like
six, nine months, we've made allour teams AI teams. So we've
made this investment in buildingup the fluency in the entire
team. And so that means goingfrom student to teacher really
(18:42):
fast for our experts who haveonly been AI experts for a few
years in this new world.
And so, we've been giving them alot of guidance. One of the
things that we've been sayingquite a bit is, you know,
there's this confusion with AIbecause, you know, on one hand,
the the sort of hype cycle whichhave have you telling us that
(19:02):
super intelligence is around thecorner and this stuff is genius.
And on the other hand, you know,you've got this sort of alien
technology that can pass the barbut struggles with arithmetic
sometimes. It's It's really hardto reckon those two things. A
lot of the opportunities arejust, you know, this is
technology that gives computerscommon sense.
And yeah, it doesn't have to begenius, but you can do a lot
(19:24):
with computers that have commonsense. And there's so many edges
that we can round off of thesesystems that I think we're all a
little blind to because we justtake the sort of like lack of
flexibility that computers bringfor granted. And so even in
elation, we're kind of rewiringour own brain and sort of like
reminding ourselves nobody wantsfeatures. Nobody asked us to
(19:46):
build features. They're notvirtuous.
People asked us to get theirjobs done and have joy in their
work and to be effective in whatthey're trying to do. And so
we're sort of going back tofirst principles on a lot of
these workflows and saying howmuch of this is here because
computers didn't have commonsense. And if we reimagine these
surfaces completely AI native,let's try to pretend, for
(20:09):
instance, that we were born withthat smartphone in our hand,
like, what would this look like?
Daniel Williams (20:13):
Yeah. Last thank you for answering that.
Last question. I see over yourshoulder, there's an emblem
there, Elation. I have somenotes here.
It was recently awarded best inclass for small practice
ambulatory EHR PM. At MGMA, welove celebrating along with our
partners, with our MGMA members.Talk about that award and what
(20:36):
went into it and, you know, howyou're kinda riding that wave
right now.
Phill Tornroth (20:41):
Yeah. We're super we're super grateful to to
have that, to have gotten thataward. The team's really jazzed
about it. Yeah, I think itreflects a lot of the hard work
that we've done thinking aboutthe experience. And one of the
things that I love about theclass surveys and those awards
is that they're out theretalking to our actual users.
(21:04):
And when we get these reportsback, get quotes and we get
feedback. And they're soconsistent with the feedback
that we solicit from our userson a daily basis that it's just
it's it's great. I've been inother companies and areas where
you wonder about some of theseawards and how much is marketing
(21:25):
fluff and does it really reflectthe experience that actual users
are having? And I've been sohappy for the the class
institution for that reason.
Daniel Williams (21:35):
Yeah. Well, Phil Tornroth from Alation
Health, thank you so much forjoining us today on the podcast.
Phill Tornroth (21:43):
Thank you, Daniel. Yeah, I really enjoyed
it. Would love to be backsometime.
Daniel Williams (21:47):
Yeah. You may see me show up in San Diego. Can
go get I'll a cup of
Phill Tornroth (21:52):
be here.
Daniel Williams (21:53):
For all of our listeners, what we're going to
do is we're going to put somelinks and resources to the
things that Allation Health aredoing out there in healthcare
and how they can providesolutions for you at your
medical practice. Until then,thank you all so much for being
MGMA podcast listeners.
Well, hi, everyone, and welcome to the
MGMA Business Solutions Podcast.I'm your host, Daniel Williams.
I'm a senior editor at MGMA andpretty much the host of the MGMA
Podcast Network. So you've seenme on here before. Today, we are
really excited.
We have a new guest here, PhilTornroth. He is a vice president
(00:23):
of engineering at AlationHealth. Phil's been innovating
in healthcare technology forover two decades and helping
build tools that reduceclinician burden and bring human
centered design to theforefront. What we're going do
is get to know Phil a little bitbetter, get to know a little bit
better about Alation Health, butalso something that's exciting
(00:46):
and on the top of mind for a lotof people, getting to understand
what is going on with AIdevelopments out there and how
they can support primary careclinicians. With all of that
said, Phil, welcome.
Phill Tornroth (01:01):
Thank you, Daniel. Happy to be here.
Daniel Williams (01:02):
Yeah, so good to have you here. We have a
connection. You're in the SanDiego area. I've got a daughter
in college down in that area, soit's really good. Maybe I'll
swing by and say hey to yousometime.
I never need an excuse to go outto San Diego. I love it there.
Phill Tornroth (01:18):
Yeah. Me too. Weather's great here right now
too.
Daniel Williams (01:20):
Yeah. So let's start out, Phil, just getting to
know a little bit about yourbackground. I I shared some
information, but what are somethings that you might wanna
highlight for our audience sothey could just get to know who
you are?
Phill Tornroth (01:34):
I've made a career in health care startups.
Those that those are basicallythe two through lines for for my
career mostly is almostexclusively in healthcare and
almost exclusively at relativelyearly stage venture startups. I
did the sort of first half ishof my career, specifically
focused on patient safety andpreventing medication errors in
(01:56):
hospitals. And I think that gaveme like a good sense of why I
wanted to work in healthcare.And I'm really grateful to have
had such a mission driven start.
I think maybe if I had startedin like hospital billing or
something, I could have run forthe hills. And then for the last
fifteen years, I've been focusedmostly on independent primary
care with Alation.
Daniel Williams (02:16):
Okay. I have to ask you. We're gonna get more
into AI, but is anything goingon in AI surprise you? Or do
were you enough into that fieldwhere you went, this is the
direction it's going? Did youhave any inkling?
Phill Tornroth (02:31):
No. It surprised me. The the truth is I so my my
real AI awakening in terms ofwhat we're gonna be able to do
practically in the relativelyimmediate term, I think, came,
like mid twenty twenty three.
Daniel Williams (02:46):
Okay.
Phill Tornroth (02:47):
And before then, I you know, I was paying some
attention to machine learning,but I didn't see us rounding the
corner as fast as we have. Andin truth, I've always been like
a little bit of a of a Ludditewhen it comes to new technology.
I like to see it work before,you know, I get too excited
about it.
Daniel Williams (03:08):
Yeah. That is so cool to hear from someone who
has a technology background thatyou're not just right there at
the forefront with everything,every new gadget and, iteration
that comes out. So that is I'mnot the only one. Let's learn
more about Alation Health. Iknow that you guys are a partner
of MGMA, and we're great to soglad to have y'all on board with
(03:31):
us.
But what I'm seeing here is thatAlation Health supports over
36,000 clinicians and is knownas the largest community of
primary care innovators. Tell usa little bit about Alation
Health. What do our listenersneed to know? Our listeners are
those medical practice leadersand decision makers.
Phill Tornroth (03:51):
Well, first of all, founding story is pretty
powerful and had a lot to dowith me joining. So Kina and
Conan were our founders. Andthey have a father who's a
practicing primary carephysician who just retired from
his practice but worked for manyyears in Walnut Creek. This was
(04:11):
around the time that likeMeaningful Use was showing up
and there was an enormous amountof incentivizing providers to
get off of paper and onto theseEHR systems. And they helped
their dad survey the field ofwhat was available and came to
the conclusion that thesesystems were going to be really,
frankly, existentially terriblefor these, especially these
(04:34):
small primary care physicianslike their father who provided
really complex proactive care toa panel of 1,200, 1,300
patients.
And the company was founded onthe belief that primary care is
our biggest lever againstdownstream illness and costs,
(04:57):
and that it's frankly, likeundervalued as an opportunity.
And that attention would turn inthat direction and that
technology was not on track tohelp provide leverage. So we
started Alation to focus veryspecifically on that.
Daniel Williams (05:13):
Okay. Give us an idea then. What time frame
are we talking about? When wasthat?
Phill Tornroth (05:18):
I think they started working on it 02/2009,
and then I joined as the firstengineer in 2010.
Daniel Williams (05:24):
Okay. All right. I wanted to follow-up
then about that work withprimary care. So how does this
community of Alation Healthsupporters, supporting over
36,000 clinicians, how does thiscommunity influence your
approach to integrating AI toolslike Note Assist into your EHR
(05:45):
platform?
Phill Tornroth (05:46):
Yeah. I mean, it was one of the things that we
would talk about a lot is havinga clinical first strategy.
Daniel Williams (05:52):
Okay.
Phill Tornroth (05:53):
So to like sort of double click into what I was
just saying, I think when KeenanConan looked at why technology
wasn't providing as muchleverage to clinicians as it
ought to, and as it did inplenty of other verticals where
technology was really reshapingworkflows, one of the things
that they noticed is thatvirtually all EHR companies are
(06:15):
billing companies at heart, andthen maybe eventually get around
to building an EHR or buying anEHR, but their focus is really
on billing. And we decided firstand foremost to take a clinical
first approach and focus firston what do providers need in
order to make this reallypowerful diagnostic tool,
because that's what the chart iswork for them. And how can we
(06:38):
add leverage? And when it comesto AI, a lot of our thinking is
centered in that same placewhere the first place we go is
what clinical workflows looklike, and in what ways could
this technology reshape andenhance those. And sometimes
that also means investing inbilling.
(06:58):
We have a billing platform andan all in one solution today,
but it mostly centers us andwhat do providers start the
practice to do? And how can wemake that as joyful and
efficient as possible? And howcan we make as much of the other
stuff go away?
Daniel Williams (07:13):
Okay, thanks so much for that Phil. Now, in
reading about Alation, the EHRplatform is known for its
intuitive design and the waythat has unified work flows. So
when we think about it that way,how are you designing the
products? How are you designingthings that can be implemented
for those medical practiceadministrators and other people
(07:36):
in healthcare?
Phill Tornroth (07:38):
Yeah, when we talk about unified workflows, a
big observation we have when welook at systems and features
that are failing in healthcareis that they often feel
compartmentalized. I think insome cases, the teams working on
these might shift their orgchart a little bit. So, you
know, really one of the keyinnovations in Elation early on
(07:59):
was just making it possible tosee disparate pieces of data at
the same time to be able to lookat a patient's medication
history next to your last visitnote or review historical
records while referencing yourown. So when we talk about
unified workflows, a lot of itis thinking about what the
purpose of this is first, andthen designing surfaces that
(08:20):
support that clinical workflow.We made the decision last year
to really lean in on AInatively.
And so by that, I mean, we hireand train and build these skills
in house versus dependingentirely on partners to build
solutions on top of our system.And one of the reasons is that
(08:41):
we really firmly believe wewon't be able to accomplish
those unified workflows in areally graceful way and
incorporate AI the way it shouldbe incorporated without doing
that. If we depend entirely onpartners, we're going to get
little pieces of the puzzle thatdon't really connect to each
other.
Daniel Williams (08:57):
Right. I noticed that earlier I I
mentioned the term note assist,and I didn't get you to
elaborate or define that. And sowe're just talking about it like
everybody listening. Oh, yes. Ofcourse, Noticist.
What is Noticist first? And thenI have a follow-up for one of
your new innovations in thatprogram.
Phill Tornroth (09:15):
Yeah. So Noticist was our our flagship AI
product that we launched lastyear. It's a natively built AI
scribe integrated directly Andinto so that means that it
records and transcribes yourconversation with the patient.
And in real time, every fewminutes or so, it transforms
(09:38):
that into note content. Itrespects your visit note
templates, and it'll fill themout for you.
It respects the problem listsand incorporates context that's
already in your chart. So itbecause it's natively in the
application, it has all thatcontext and you're not cutting
and pasting and assembling thisinformation from another tool.
Daniel Williams (09:57):
Okay, that is so helpful. So my follow-up is a
note I had from you is one ofyour latest innovations is
something called Actions. I feellike I'm talking to, you know,
somebody from Apple or somethinghere. It's all these really cool
iterations and new products. I'mjust I'm so excited about it.
I love this stuff. What isactions? What is that?
Phill Tornroth (10:20):
Yeah. Actions was a logical next big step for
us. Know, one of the greatthings about Noticist is that
you can focus on your patient.And we have a lot of doctors
that tell us like, this isamazing. I don't have to keep
jotting things down and usingthis half of my brain to reshape
information.
I can stay focused on mypatient. But one of the things
(10:42):
that we still saw providersdoing is needing to either like
review their note and make surethat they caught every to do
item that they needed to followthrough on, or some of our
providers would actually likehave gone back to a piece of
paper and we're keeping like achecklist in front of them. And
so what actions does is itlistens to all of the things
(11:02):
that you intend to need tofollow-up on in that visit. So
if you talked about refilling aprescription or changing a
dosage or sending a lab order,and also the things that might
not be as top of mind, like ifearly in the visit, you'd
mentioned that you were going toget the patient like a handout
on a certain set of exercises orwhatever. So we keep all of that
in the to do list.
And at the end of your visit,you've got it there. If you take
(11:26):
actions in the application, sofor instance, if you go to our
EHR and you write thatprescription, we notice that you
write it and we check it off foryou. And so it's this live list
of the things that you intendedto follow-up on.
Daniel Williams (11:38):
Okay. This may be a simplistic question, but I
I need to ask it for myself andhopefully for some of our
listeners here. When I work withAI and prompt and do that those
sorts of things, sometimes I'mnot getting the results I want.
So then but I know what I'mlooking for. So I go, no.
(11:58):
That's not exactly what I'mlooking for. Let's shift it
here, here, and here. Now you'redescribing when y'all are
building out your program, yourAI, you're doing that natively.
So how do you ensure that it'sgathering the information that
you need? That's something thaty'all are building into it on
the front end, or is itsomething where someone comes
(12:20):
back like a medical assistant orsomeone just to make sure that's
all being integrated, all thosenotes are being done the right
way?
Phill Tornroth (12:28):
Yeah, so our tools right now, the ones that
we've shipped are prettyagentic. So the AI listens,
records, remembers what you do.In terms of making sure that's
accurate, I think there's twobig levers that we talk about
and use as a team. One is we doquite a bit of pre formal
(12:48):
evaluation. So we build corpusesof data and we run through
enormous numbers of test casesand we're constantly iterating
and trying as new models comeout and things.
That's really important to us.And it's actually most of the
time and effort that our AIteams spend on these features is
writing and running those evals.The other lever that we use is
(13:10):
design. So building with AI isreally like designing for
failure and iteration and howcan we make like one of the sort
of jokes that's become a mantraon the team is this there's this
Mitch Hedberg joke about howescalators don't break, they
just become stairs. And so wetalk about that a lot on the
team is like, how can we designan experience where we make
(13:34):
failure safer?
Because these tools are gonnaget it wrong sometimes. And so
can we design a surface and anexperience that allows the
provider to still be in control,see what happened, recover from
these situations?
Daniel Williams (13:47):
Okay. Love that. Thank you for clarifying
that. So let's move to the nextstep here. Technology, as we
know, can help so much withworkflows, but can also if
somebody's not tech savvy, someof our healthcare professionals
aren't just up on the latest,greatest technology that's out
(14:07):
there available to them, wedon't want to disrupt workflow.
So how do y'all integratethings? How do you design it so
that it doesn't actually impedethe efficiency in the practice?
Phill Tornroth (14:19):
Yeah, absolutely. Mean, we do think
about that quite a bit andmaking sure that these
experiences have, like we'lltalk sometimes about these
experiences having off ramps oron ramps and like our, since
we're all learning how thistechnology is going be
integrated into our lives, andthere's such a variance in
fluency, we think a lot aboutmaking sure that these are
(14:42):
experiences that you can dip inand out of or that we have ways
for you to learn about themsafely. Yeah, also, you know,
the point about tech savviness,like I mentioned, I'm kind of a
bit of a Luddite and come lateto these things. One of the
things that I found so inspiringabout AI specifically is that
that adoption curve is kind ofreversed. Really early on when
(15:04):
we started working on Notisyswith some of our customers, I
talked to a couple customers whoran clinical teams, and they
were finding that the biggestadopters of these tools, the
people who latched onto them thefastest were the ones that had
the hardest time using acomputer.
Daniel Williams (15:22):
Wow.
Phill Tornroth (15:22):
Makes sense. These are providers that have
been on paper their whole life.And now the idea that they can
talk to their patient as opposedto having to click and type
through this note, It was just amuch more human experience for
them. So I've continued to seethat even on our own teams, and
I love that about thistechnology in particular.
Daniel Williams (15:43):
Yeah. And that that leads into the next
question I have for you. I havea note down here that you
describe yourself as a reluctanttechnologist and really with
your focus on human centereddesign. So let's talk about
that, you being a reluctanttechnologist, and then how that
goes into the products that youbuild out.
Phill Tornroth (16:04):
Yeah. What it means is I I've never really
been enamored by technology fortechnology's sake. I've always
been much more of a product anddesign person who happens to do
software engineering as a trade.And so don't worry, I hire and
employ lots of people who arefascinated with technology and
(16:24):
they're the ones that push me tolook at things and adopt. I'm
mostly the the the sort of like,person that, like, puts the
brakes on and asks, like, can weshow value with this yet?
Like, is this is this gonna makea real impact on real people and
push us to experience that?
Daniel Williams (16:41):
Yeah. I've got a couple more questions for you
before we sign off. So as we allknow, I have conversations
almost daily with peers, witheverybody I interact with. I had
this conversation recently withsomeone. I've only had a
smartphone for about fourteenyears, but I'm not young, and I
don't remember life beforehaving a smartphone.
(17:03):
I was telling you offline that Iwas just in Spain, and so I
didn't have a a SIM card. Iwasn't connected, you know,
where I was. So I actually had adetox of the smartphone, the
device, everything because Iwasn't staring at it every five
seconds. You know? I've adoptedback.
I'm back to staring at it. Butwhat I wanted to get to was with
(17:25):
AI, as you were saying, youradoption was around '22, '23 of
you know, just a few years ago.And we're already like, well,
what would I do without AI infront of me? And it is evolving
so rapidly. Where do you see itgoing, you know, in just the
near future?
Where are you looking around thecorner? What's your team doing
(17:46):
as far as where you think it canreally make seismic shifts in
health care in a good way?
Phill Tornroth (17:54):
Right. It has been so fast. And there's so
much opportunity that Isympathize. Like, I think a lot
of us just sort of want to,like, hit pause and breathe and
try to figure this out together.It's super exciting.
And it's super exhausting all atonce. One of the things that
we've been looking for isespecially now that we have, you
(18:18):
know, we went through thisprocess of building an AI team
at Alation, which I think a lotof companies did and build their
expertise in one team and thatteam built and shipped note
assist and shipped actions. Andthen really over the last like
six, nine months, we've made allour teams AI teams. So we've
made this investment in buildingup the fluency in the entire
team. And so that means goingfrom student to teacher really
(18:42):
fast for our experts who haveonly been AI experts for a few
years in this new world.
And so, we've been giving them alot of guidance. One of the
things that we've been sayingquite a bit is, you know,
there's this confusion with AIbecause, you know, on one hand,
the the sort of hype cycle whichhave have you telling us that
(19:02):
super intelligence is around thecorner and this stuff is genius.
And on the other hand, you know,you've got this sort of alien
technology that can pass the barbut struggles with arithmetic
sometimes. It's It's really hardto reckon those two things. A
lot of the opportunities arejust, you know, this is
technology that gives computerscommon sense.
And yeah, it doesn't have to begenius, but you can do a lot
(19:24):
with computers that have commonsense. And there's so many edges
that we can round off of thesesystems that I think we're all a
little blind to because we justtake the sort of like lack of
flexibility that computers bringfor granted. And so even in
elation, we're kind of rewiringour own brain and sort of like
reminding ourselves nobody wantsfeatures. Nobody asked us to
(19:46):
build features. They're notvirtuous.
People asked us to get theirjobs done and have joy in their
work and to be effective in whatthey're trying to do. And so
we're sort of going back tofirst principles on a lot of
these workflows and saying howmuch of this is here because
computers didn't have commonsense. And if we reimagine these
surfaces completely AI native,let's try to pretend, for
(20:09):
instance, that we were born withthat smartphone in our hand,
like, what would this look like?
Daniel Williams (20:13):
Yeah. Last thank you for answering that.
Last question. I see over yourshoulder, there's an emblem
there, Elation. I have somenotes here.
It was recently awarded best inclass for small practice
ambulatory EHR PM. At MGMA, welove celebrating along with our
partners, with our MGMA members.Talk about that award and what
(20:36):
went into it and, you know, howyou're kinda riding that wave
right now.
Phill Tornroth (20:41):
Yeah. We're super we're super grateful to to
have that, to have gotten thataward. The team's really jazzed
about it. Yeah, I think itreflects a lot of the hard work
that we've done thinking aboutthe experience. And one of the
things that I love about theclass surveys and those awards
is that they're out theretalking to our actual users.
(21:04):
And when we get these reportsback, get quotes and we get
feedback. And they're soconsistent with the feedback
that we solicit from our userson a daily basis that it's just
it's it's great. I've been inother companies and areas where
you wonder about some of theseawards and how much is marketing
(21:25):
fluff and does it really reflectthe experience that actual users
are having? And I've been sohappy for the the class
institution for that reason.
Daniel Williams (21:35):
Yeah. Well, Phil Tornroth from Alation
Health, thank you so much forjoining us today on the podcast.
Phill Tornroth (21:43):
Thank you, Daniel. Yeah, I really enjoyed
it. Would love to be backsometime.
Daniel Williams (21:47):
Yeah. You may see me show up in San Diego. Can
go get I'll a cup of
Phill Tornroth (21:52):
be here.
Daniel Williams (21:53):
For all of our listeners, what we're going to
do is we're going to put somelinks and resources to the
things that Allation Health aredoing out there in healthcare
and how they can providesolutions for you at your
medical practice. Until then,thank you all so much for being
MGMA podcast listeners.
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