October 8, 2025 • 52 mins
AI has the potential to revolutionize healthcare—but it’s not just about smart algorithms or automated diagnoses. It’s about earning trust in high-stakes environments where lives are on the line. Galen sits down with David Doan, Director at Kyndryl and former registered nurse, to explore how delivery leaders can navigate the clinical, technological, and ethical challenges of implementing AI in healthcare.
From preserving human judgment and connection to aligning regulators, executives, and frontline clinicians, this conversation digs into the realities of AI-powered healthcare delivery—and what project leaders can do to make it actually work.
Resources from this episode:
- Subscribe to the newsletter to get our latest articles and podcasts
- Connect with David on LinkedIn
- Check out Kyndryl
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Galen Low (00:00):
What role do project leaders play in
(00:03):
building this trust withinAI healthcare projects?
David Doan (00:06):
Project managers are not just task master.
They should be framing anAI project as not just a
technology deliverable, butit's a human-centered change.
It's integrating thattechnology with what I call
humanizing the AI project.
Galen Low (00:20):
Why is it so important that healthcare
finds ways to adopt AI?
David Doan (00:24):
What is that stake ultimately is more than
efficiency and effectiveness.
This has a directimpact to patient care.
If that adoption fail, there'sa grave risk of patients
may miss out on potentiallife saving interventions.
There may be misdiagnosis ifthe predictive of modeling
does not make sense,especially if AI models are
(00:47):
trained on incomplete data.
Therefore, the marginalizedpopulation may face
worse health outcomes.
Galen Low (00:54):
Healthcare is so interesting because
it's that rigor by default.
It has that many stakeholderswith that many different
perspectives, and so it's almostone of the most complex versions
of the game of implementing AIto create solutions that drive
better outcomes for humans.
(01:15):
Welcome to The Digital ProjectManager podcast — the show that
helps delivery leaders worksmarter, deliver faster, and
lead better in the age of AI.
I'm Galen, and every week wedive into real world strategies,
new tools, proven frameworks,and the occasional war story
from the project front lines.
Whether you're steeringmassive transformation
projects, wrangling AIworkflows, or just trying to
(01:36):
keep the chaos under control,you're in the right place.
Let's get into it.
Okay, today we are talkingabout the immense potential
of AI in healthcare and whatproject leaders can do to build
trust, raise risks, championethics, and ultimately drive
patient outcomes through AIpowered healthcare projects.
(01:56):
My guest today is DavidDoan, Director, Consult
Partner for Healthcare& Government at Kyndryl.
David is a healthcaretechnology and business
transformation leader withover 30 years of clinical
and consulting experience.
He started his career at thebedside as a registered nurse
for the first 10 years andthen went on to consult at
McKesson, Accenture, Ernst& Young, and is now partnering
(02:19):
with C-Level and IT executiveclients to drive strategic
digital transformation, AIinnovation, and value-based
care initiatives at Kyndryl.
Beyond that, David is thepresident of PMI Los Angeles
chapter, serves on the boardof directors of five other
nonprofit organizations, is amentor for the Asian American
Professional Association,and so far that's only
(02:40):
half of his rap sheet ofaccolade and accomplishments.
It's very impressive, David.
Thank you for being on the show.
David Doan (02:46):
My pleasure, Galen.
Absolutely.
Galen Low (02:49):
I know we zig and zag and like as we
were preparing for this,we covered a lot of ground.
For this episode, I'm hopingthat we can just cover just
the excitement and the fearsurrounding AI enhanced
patient care and what canbe done to address both.
Maybe just like what's at stakefor our healthcare industry
if we don't get AI, right?
How a framework of trust canhelp project leaders align
(03:12):
disparate stakeholder groups.
And maybe just how projectleaders would know previous
healthcare experience canget into the healthcare
space and maybe vice versa.
How does that sound to you?
David Doan (03:23):
That's wonderful.
Great discussions,great questions.
I have my work cut out, butI'm pretty sure I can provide
a little bit of insightbased on my experience.
But yeah.
Great discussion.
Galen Low (03:34):
Well, if I learned anything about you so far,
it's that you're fast on yourfeet and you know your stuff.
So I'm gonna challenge you.
I'm gonna challenge you.
We've got this tradition herewhere I kind of start with
like the big question, theone hot question that we can
then sort of zoom out from andthen build the context around.
So my big question is this,what is the biggest fear
(03:54):
that clinicians and medicalpractitioners have when it comes
to AI being introduced intothe way that they deliver care?
David Doan (04:01):
Yeah, great questions.
Very relevant one.
I summarized it inkind of two topics.
One is the fear of losing humanconnection and judgment is one.
So I touched on that.
And the second is reallythe fear of accountability.
So I actually started mynursing career writing.
(04:22):
Literally writing, you know,there's no such thing as an
electronic health record orelectronic medical record.
And when we move intotechnology, even just giving
medications out of thismachine called Pyxis Machine,
we always were fearful of howis that going to disconnect
us with the patient somehow.
AI is definitely anotherexample of advanced technology
(04:44):
that can actually do that.
So for example, now there's a AItool, machines and predictive,
you know, machines that canactually read the film from
a chest x-ray or a PET scan.
So there's that fear of notbeing able to actually, you
know, touch and feel and havingthat human connection and
also the judgment as you know,you know, medicine, nursing.
(05:07):
It's certainly a science,but it's a lot of art and
that requires a lot of data,clinical data, nonclinical
data, and in the last pieceof the puzzle in healthcare is
really the clinical judgment.
That's really what differentiatebetween a nonclinical staff
versus a clinician that has,you know, a license that they
need to practice at the top ofthe license, but also a sense
(05:29):
of accountability as well.
So I think that the fearwhere AI can actually replace
conversations and dialogues withpatients at the bedside, or even
when you adopt visiting a doctorvisits or even sometime when you
have telehealth or telemedicine,is that they fear that they
cannot and should not lose.
Really the clinical judgmentand their decision making.
(05:52):
So whatever technology ortool, that is one thing that
we need to really address andit needs to be collaborative
with the clinicians.
So algorithm thatspit out predictions.
They need to make sure thatthe data is insightful at
the point of care, but reallyappreciate the need for the
clinician to understand andtrust the data and the insight,
(06:14):
but really preserve thatsacred clinicians and patient
relationships, so that waythey're still somehow providing
data, clinical judgments thathelp inform the decision making.
The accountability piece isimportant too because you
know in medicine, cliniciansare trained to do no harm.
We wanted to make sure thatthe AI or technology model
(06:36):
actually works, and thatway it makes recommendations
that it is consistent,aligned with evidence-based
guidelines and all of theother reputable professional
organizations recommendations.
That accountability reallyrests on, can clinicians
still have that final reviewto make sure that they still
ultimately accountable forit, but the AI system, or the
(06:58):
technology and the engineeraround that, there has to be
some due diligence to ensurethat data is not false, to
help ensure that trust as well.
That's a little bit long-winded,but I would say two really
fears that if you break itdown, is really about the human
connections or making sure thatthere's no loss of that, and
that also the clinical judgment.
(07:20):
And second is the roleof accountability of a
clinician, but also fromthe technology side.
Galen Low (07:26):
I love that and like I like that you framed
it around the fact that it'slike an art and a science.
Right.
And I think sometimes it'seasy to get swept up from
a very high level of, oh,it's just information.
We can upload all of ourmedical knowledge and then that
information will be available.
But I also like the otherthing you did there, which
I don't know if you meantto do it, but there have
been a lot of disruptivetechnological progressions
(07:49):
in the healthcare industry.
You mentioned some ofthe prescription apps.
We're talking about telehealth.
There's been a lot ofthings, and I think.
What I like about youranswer there is that these
are the underpinningsthat have helped us get
through all of this change.
And I know like EHR, like theelectronic health records or
electronic medical records, it'sbeen a long journey, hasn't it?
(08:10):
Right.
At my time in consulting,we're still transitioning
systems over.
In some ways.
It's not justtechnological progress.
It's like we're still buildingtrust and we're still being
careful because of that oath,because we can't just assume
that something that happens ina black box is gonna work well
every time or 90% of the time.
(08:30):
Like that isn'tquite good enough.
It's the judgment andit's the sort of humanity
that needs to stay in it.
I think it's fascinating.
And then also I just thinkthat idea of the consistency,
you mentioned consistency, andimmediately my head went, oh
yeah, hallucinations in AI.
It's fine in my work, right?
It's like, wait, hold on.
(08:50):
That was not the answerthat I was looking for.
Or even I asked it the samequestion three times and
got three different answers.
That's fine, I can fix that.
But like when it comes topatient care, that is something
that we have to do very Right.
And I'd be very carefulabout, so I know that's
all the Right, yeah.
Important things.
But I wondered if maybe we couldzoom out a little bit because.
(09:13):
We've been talking a littlebit about accountability and
trust, the patient experienceand the humanity of it.
We talked a little bit alongthe way about sort of some
technologies and technologyalways does find its way into
healthcare for good reasons.
AI seems a little bit differentin some ways, or maybe it's
not, but I thought maybe I'djust kind of ask why is it
so important that healthcarefinds ways to adopt AI?
(09:35):
What's at stake here and what'slike the biggest barrier that
AI adoption faces in healthcare?
David Doan (09:41):
What is at stake ultimately is more than
efficiency and effectivenessof how clinicians interact
with their member or patient orthe healthcare delivery team.
'cause there's a whole teamthat managed the patient is
ultimately, really result topositive or health outcomes.
(10:03):
So there is suchbig ramification
and consequences andconsideration to think about.
It's not just makingsomeone's workflow easier,
having a better experience.
Ultimately this has a directimpact to patient care.
And then that patient care,even though it's one-on-one
with the practitioner at a time,it actually ultimately results
(10:25):
in what I call on a massivescale called population health.
And it also aligns with.
The quintuple aim, where it'snot just about costs, it's not
just about access, it's nowabout the clinician experience,
the patient experience.
And finally, at the tip,which is the fifth kind
of layer of this kind oftriangle is health equity.
(10:49):
So where does AI come into that?
AI can definitely, certainlypredict the diseases taking
in so much data, the clinicaldata, the claims data, the
nonclinical data, the publiclyavailable data and so on.
All of that helps to predictwhich patient cohort or
populations that the providersor the health plan or payer
(11:11):
can identify quickly tointervene to kind of slow the
progression of any diseasestate chronic conditions.
Now if that adoption fail,what you can see is there
are patients that should bemanaged and they're not, or
they have been identified ofhaving something that they are
not they're not appropriate.
(11:31):
There's also an opportunitywhere there's a grave risk
of patients and membersmay miss out on potential
lifesaving interventions.
There may be misdiagnosis ifthe machine or the modeling
tool does not make sense.
And when we think abouttechnology, there's also a lot
of people who don't live inlarge metropolitan cities, in
(11:53):
rural populations where there'scritically accessed hospitals.
We are still beingchallenged with technology.
The technology may be available,but the 5G connection and
network connection, theinternet connection, or how
do we actually manage that?
And when I talkabout health equity.
Are you expecting someonewho English may be their,
not their first language,but they also are challenged
(12:15):
because of dexterity, levelof education or age and so
on to be able to use whatevertelehealth medicine it is?
So when you talk about AI,there's a huge implication
in what's at stake isultimately the health
outcomes of the population.
The biggest barrier, I kindof alluded to it, is a lot
of it is there's technologybarrier from the receiving
(12:39):
of the receiver of carethat's your patient's member.
But if I were to focuson the clinicians and the
care deliverer and also thecaregivers, is that really
that trust we talk about?
But from a technology side,information needs to be
interfaced or integrated andimmersed into the workflow.
So if it's not immersed inthe workflow, AI may force
(13:02):
the clinician to use anothertechnology, or you have to
have a little thing thatto record the conversation.
Where does that information go?
Does it actually immerseor present it in what
I call the naturalworkflow of the clinician?
Because if it does not presentitself in that workflow,
that is really seamless.
It's not gonna increase theadoption of the usage of
(13:26):
the whatever the technologyis, because anything that
disrupts the clinician timewith patients that will
result in poor adoption.
And lastly, you know,there are biases.
So if AI models are trainedon like incomplete, you know,
lack of data or the data isnot normalized, standardized,
or skew in some way, thereforethose are the opportunity
(13:50):
where patients could.
Especially the marginalizedpopulation may even face
worse health outcomes.
So that's what's at stake ismassive about health outcomes
and then also the adoption ofclinicians with technology.
Galen Low (14:06):
I'm really glad you went there, especially
with the patient andclinician experience.
My background's in user-centereddesign, so like mostly we're
like digital solutions that.
Yes.
You know, solve a problem,make something more
efficient, leverage moredata, but also fundamentally,
yeah, have to be workable.
Have to enter into a workflowseamlessly so that it doesn't
(14:27):
create an additional barrier.
And you were saying up top whenyou were a registered nurse,
you're doing bedside care.
You know, you're writingthese things by hand.
And there is an opportunityto really give some of that
time back right to a medicalpractitioner so that they
can focus on patient care.
At the same time, not addinglike an additional step in there
(14:49):
that might actually lead toworse outcomes or lead to more
challenges in delivering care.
And that health equity thing,I hadn't really thought of
it in that way, but like Iwas chatting with someone
last week, we were talkingabout how AI is sort of, it
kinda like levels the playingfield in some areas, right?
Where right now there's peoplewho are vibe coding, they've
never been developers before.
(15:10):
They didn't train to be adeveloper, but now they're
able to create an applicationand vice versa, right?
Technical folks who weren'ttaught or don't consider
themselves well versed inlike business language now
can sort of use some ofthese tools available to
them to sort of have thoseconversations and like break
down some of the silos.
And I did a little bit ofwork in like outpatient
(15:32):
care, telehealth sort ofstuff from a digital side.
And it really opened my eyes.
I think you, what you said aboutfolks living in metropolitan
areas versus bulk of thepopulation, which doesn't, you
know, we're scattered about.
The infrastructure is different.
The United States in particularhas been pretty aggressive about
getting broadband everywhereand the 5G transformation.
(15:54):
But it's still not everywhere.
We can't just assumethat everyone has access
to all these things.
Has the ability to engage withall these things is open to
all of these things, and Ithink that's the big zoom out.
Why I think it's superinteresting in the healthcare
side of things, because unlikesome of the things that we
talk about in the businessworld where we're like.
Hey, we can get copilot,you know, to be helping
(16:16):
us write documents.
We're all sort of a certaintype of knowledge worker
doing a certain type of job.
Healthcare is not that.
Healthcare iseverybody, you know?
It impacts everybody.
It goes across demographics,it goes across, yeah, a lot of
different things, and that's whyI think it's such an interesting
and juicy topic because evenif you're not in healthcare,
if you're listening to thisand you're not in healthcare.
This at least shows thatpicture of AI at scale, right?
David Doan (16:39):
Absolutely.
Galen Low (16:40):
With different members of the population
for something that reallymatters, which is the health
of our population, patientoutcomes, and ultimately health.
I did like also what yousaid about preventative.
It kind of got me thinking,you know, predictive
analytics, right?
It's one of those thingsthat, you know, a lot of
businesses are like, yeah,they've been on it for years,
so that they can anticipate.
And then I start thinkingabout things like.
You have your health spendingaccount to get like an
(17:02):
ergonomic office chair.
In some ways, that'spreventative care because
it's like, okay, if you'renot sitting in a garbage chair
all the time, then you're notlikely to develop back pain,
chronic back pain that then weneed to treat in a certain way.
And then I started thinkingabout strain on system and
I'm like, okay, well thereare health administrators,
healthcare leaders, and evenjust the business side of the
(17:22):
system going, wow, that's great.
Yes, we wanna prevent.
Some of these thingsfrom getting too far.
You said, you know, interventionat the right time to get
people the care that they need.
And I'm also like, well, someof the folks, don't get me
wrong, noble in intention aswell, but it's their job to
also think about strain onsystem and like money, right?
To be like, well, it gets alot more expensive to treat
(17:43):
people later in their healthjourney, whereas if we catch it
early, that could be cheaper.
Then it got me thinking, becauseyou actually are someone who
did a decade at bedside asa registered nurse before
entering the consulting world,and now you work with chief
medical officers, you workwith regulators, you work with
other decision makers in thehealthcare space, but in other
(18:06):
words, like you actually aresomeone who can see things
from all the perspectives.
It got me thinking about liketrust, but also how can trust
around AI be built betweenpatients and caregivers and
clinicians and regulatorsand business leaders.
They all look at it froma bit of a different
perspective and like what'sinvolved in reconciling
all those perspectives.
David Doan (18:26):
Yeah.
You are making mework very hard.
But Galen I'm delightedto share my perspective
on the hard question.
You know, just by youlisting all of those names
of what I call stakeholders.
So in healthcare,it's never a person.
It's always what I calla healthcare ecosystem.
And that ecosystem may be peoplethat are likely invisible to
(18:48):
the patients or the members.
Like for example, youmentioned about regulators.
So there's accrediting bodies.
There's also centers forMedicare and Medicaid services,
or CMS and the Center forDisease Control, et cetera.
They want governance andthey wanna make sure that
ultimately the care that isbeing delivered, whether you
use advanced technology or notechnology, is actually, you
(19:11):
know, quality and is safe.
And you also have thepatients who want reassurance.
Reassurance that you providepractitioners or doctors.
Even know about the culturethat I am raised up or the
language that I speak, becausethat has a lot to do with the
type of food and nutritionsthat I have a preference on.
(19:31):
Obviously clinicianswant to see evidence.
They are trained toreally review what we
call peer review articles.
It's not just word of mouththat, oh, the CIO or the
chief digital officer ordata officer said that we
need to adapt ambiance.
You know, listening AI,that's great, but what's the
evidence as far as has therebeen done any research that
(19:54):
shows actually there is a highprobability that is correct
versus how do we address.
Some of the hallucinations, youknow, we'll be talking about
AI or just really misdiagnosis.
So that's reassurance.
Like, I don't want tobe the first hospital
to do this, or the firsthealth plan to do this.
Has there been any evidence?
When we say evidence, it's notjust a blog, it's peer review
(20:16):
articles, and that takes time toreally build that literature up.
And then you said businessleader, I hate to say
it, it's really aboutfinancial performance.
Even in a hospitalsetting, it is a business.
So they want to see hard,quantifiable, ROI with
these very expensiveadvanced technology.
So let me just give you somesuggestions of how to bridge
(20:37):
that gap to ensure transparencyand having that shared
language to really build trust.
Because we talk about, yeah,those are the problems.
Those are the backgroundthat we have to work off of.
One is what I callexplainability.
How do you actually havethe data to really think
about in plain language?
Make the connection from atechnologist, from an engineer,
(20:58):
from a data scientist, froma product manager talk to
a clinician to say theyunderstand the business problems
and also the opportunities,meaning the specific use
cases that AI can be applied.
Can you explainhow it will help?
Can you explain how AI works?
The X, Y, Z data.
So if they understand it,you're gonna be able to get
(21:20):
buy-in, but also allow that,what I call the collaboration,
to have the clinician orthe business leaders to ask
questions because they areso busy, they don't know the
details behind the technology.
You have to talk about safeguardwith information, with data.
We have to talk about theconnectivity of multiple
data, how it gets presentedinto the workflow at what
(21:43):
I call the point of care.
Being able to explain that inlay language or playing language
on both sides, because theclinicians may be presenting
a very specific use casethat the technologist may not
understand fully what that is.
The second is really inclusionin design is you mentioned
that you have background userinterface, user experience.
(22:05):
Well, you have to have thevoice of the customers.
So who are these customers?
The patients, the nurses,the practitioner, but also
could be physical therapist,the pharmacist, everyone
and everyone else you needto really consider just
because you're a clinician,a pharmacist workflow, as
you may already know, isvery different than a nurse,
than a physicians, et cetera.
(22:26):
So those are the thingsto be considered.
The modules within an EHR isconfigured differently for
different floor and differentunit, be as inclusive in the
design and the implementationand the change management.
And then it needs to reallybe couched around governance.
People are rushed intoimplementing AI without
(22:47):
solid policies, withoutthe framework, without
the governance structure.
I know everyone talkabout framework.
Everyone has a framework ineverything, consulting firm,
but we need to carry that out.
What are some of the safeguardor the guardrails around.
Equity, fairness, bias,privacy, accountability
that we need to address.
I know that's kind of boringstuff, but without that,
(23:09):
you will not be successfulin rolling out and the
adoptions will not be there.
And also this risk on kindof the regulatory side.
And lastly is thecultural storytelling.
What is this all about?
It seems like itdoesn't fit, does it?
So how does AI improve not justthe numbers, the quantifiable
ROI, but actually patient lives?
(23:30):
Let me give you an example.
Those clients that I am ableto have the privilege of
working who I think got itright, is that they actually
tell the technology team thatwhatever you're building or
the requirements that youare writing and that you are
testing, if you don't understandhow this is used by clinician
X or business user X and howthat ultimately mapped to the
(23:54):
positive experience and healthoutcome of the patients, then
they should have no businessworking on this project.
Brilliant.
The technology team shouldbe an extension of the
clinicians or the caregiver,so they should be actually
caregivers of the caregivers.
So that is when Ithink trust is built.
So without that trust throughtechnology, you don't have
(24:16):
really the people, theprocess in place and buy-in.
So I think storytellingis about the voice of the
customer through conversation,through collaboration that
you buy-in and that willhelp with transparency and
therefore trust will be enabled.
Galen Low (24:32):
I love how that kind of.
You paint it out as anecosystem, and I think a
lot of people understandit as an ecosystem with a
lot of stakeholders in itthat you know for a cause
that really matters, right?
People's healths and livelihood.
But I love that notion oflike even like the product
team, the tech team being thecaregivers of the caregivers,
and it's all actually this.
It's one picture that differentstakeholders have to look
(24:53):
at it from different lensesthrough different lenses from
different angles, like yourchief medical officer or you
know, those are sort of businesslens on things like, yeah,
they have to care about money.
'cause guess how patientcare is delivered, right?
It requires funding, itrequires money and also.
It is something that islike very regulated, right?
We have these things in placeand it's funny, I like sort of
(25:16):
drawing the comparison to, forexample, the business world and
you and I, we both come fromthe consulting world, so I think
we can say this, but it's everyother week that BCG, McKinsey,
Accenture, EY, the publishinga report, everyone's sharing it
on social media or via email.
We're going, oh,that's a good idea.
Let's start doing thatright away versus like.
(25:36):
Has it been in a purereviewed journal?
Right.
You mentioned things likeambient AI listening, right.
And then I'm like, I haven'tbeen very close to a sort
of medical journal recently,but like what an interesting
way to sort of vet out theseideas at like the highest
rigor of very smart peoplewho understand the technology
(25:58):
and the health implicationsand the human implications.
Being critical of one anotherto sort of make sure that
this is the right thing,not just a thing we can try.
It's a completely differentpicture than how a lot
of people think about AI.
Even folks listening.
And maybe a bit of partof me is like, well,
shouldn't it be easy?
Just try and roll out alittle pilot program and
(26:18):
then scale from there.
Like, you know, be iterative.
Isn't that what we always do?
No, unfortunately, the CDCalso has to be on board, so
you kind of have to have.
David Doan (26:25):
That's right.
Galen Low (26:25):
It's a whole different thing.
But I do also think thateveryone can take a page
outta this book, right?
It's almost this like macroview of where we're heading.
We started out with AI inthe sort of business world,
in less regulated areas,just like trying stuff.
Then we're gonna run intothat governance wall, right?
We're gonna run into the dataquality wall, we're gonna
run into all these thingsthat sound boring to us now.
(26:46):
But are gonna matter foreveryone pretty soon.
And that's why I thinkhealthcare is so interesting
because it's that by default,it's that rigor by default, and
it has that many stakeholderswith that many different
perspectives by default.
And so it's almost like oneof the most complex versions
of the game of implementingAI to create solutions.
(27:07):
That drive betteroutcomes for humans.
It's really interesting.
I love that sort of framework.
I wonder if I can bringit back to the sort of
the project level as well.
I recognize you and Iwere passionate about
this sort of stuff.
Like we can talk ata very high level.
You know, we've beentalking about trust and I
kind of frame this around.
AI powered or AI relatedhealthcare projects, whether
(27:29):
that's implementing AItechnology or using it in the
project, but it is, it stillcomes back down to trust.
It's, you know, it'squite a complex picture.
What role do project leadersplay in building that trust?
Like is there a responsibilityfor folks who are delivering
some of these projects andjust like you said about.
The technologists being thecaregivers for the caregivers,
you know, what role doesa project manager play in
(27:52):
building this trust withinAI healthcare projects?
David Doan (27:56):
Well, this is a question that I'm passionate
about just because of ourkind of connection with
project management in general.
As you introduced me, I'mthe president of our Project
Management Institute of PMI, LosAngeles chapter, so I definitely
wanted to highlight some ofthe PMI concept and methodology
here in the framework as well.
(28:16):
But as far as the role ofproject managers in building
trust, project managersstrategically has been
able to orchestrate all ofthe stakeholders and all
the project team members.
So they are at a veryprivileged, critical role of
being able to see from alland all aspects, I would say
project leaders need to first bestrategic, but also be able to.
(28:41):
Make the translation so that waythe clinical, the business and
all of the stakeholders kind ofunderstand one another because
that is really important that wespeak, quote the same language.
Why would say, not justspeak, but really to
understand each other kindof needs and intentions and
requirements and all that.
And then by being thisphysician of quarterbacking.
(29:02):
You want to be able to thenfreely and proactively raise
risk early and transparently,and think of framing an
AI project as not just atechnology deliverable, but
it's a human centered change.
It's integrating that technologywith what I call humanizing
the AI project where weare reminding project team
members that is ultimatelyfor healthcare anyway.
(29:24):
I'm speaking from a healthcareindustry perspective, is
that whatever is beingintroduced that is ultimately
going to hopefully increaseproductivity, that yield
more what I call FaceTimewith the patients or members.
And that somehow wouldresult in kind of a
positive health outcomes.
I think it's all about outcomes.
That could be a whole topicof discussion, is how to even
(29:47):
measure health outcomes andwhat are the vehicles and
the data that will be needed.
So back to project management.
I have been an advocate ofproject managers on not just
task master, and we are nothere to just tell people when
to do things and how to dothings and all that, because
you can have a robot doing that.
(30:08):
I think project managers arenot being tapped into the
visionary, strategic problem,critical thinking skills.
Let me give an example.
I'm gonna reference president ofPMI, Pierre Le Manh, and he and
his team introduced a conceptcalled PMI:Next, and that was
probably about two years ago.
And I think chapters andproject leaders are still trying
(30:30):
to understand what that is.
So to me, how I interpretthat is really the vision
of what PMI or projectmanagement in general.
So what is that vision?
So we tend to say that thevision is really about.
The purpose of what it is thatwe are doing to elevate the
project success that enablessome sort of transformative
(30:51):
change in the world.
It needs to rely on strategy,being able to not just deliver
the value of tools, butenable continuous learning.
There's also kind of theculture values and then the
framework that helps supportthat vision or executing that
vision is what PMI call it MORE.
It's an acronym, MORE,which is really maximizing
(31:15):
the success through notjust traditional metrics.
We are very familiarwith what I call scope,
budget, and schedule.
But what is really the outcomeor the positive impact in
healthcare that will bepositive health outcomes?
Are we actually saving lives?
Are we actually increasingthe longevity of how patients
live, not just in number ofyears, but the quality of their
(31:39):
experiences in how they live?
Are they actuallychanging behaviors?
Those are positivehealth outcomes.
How do we organize theimpact by empowering our
professionals to reallybuild a stronger community?
And how do we reinventand reengage the
ecosystem of stakeholders?
So all these things are soimportant as what the role of
a project leaders or managershave in any project, but
(32:01):
particularly in healthcareenabling AI is really
adopting that kind of mindsetof PMI:Next and PMI MORE.
So that is the role.
A very important role of astrategic project manager has
in leading projects technologyproject in healthcare.
Galen Low (32:20):
I love that.
I love the tie in withbeing the translator, the
translating quarterback,and how it ties into like
your explainability, right?
Like there's a veryhuman element there.
Even just the fact that yousaid that like these are.
Projects that are about humans,like we need to actually
humanize technology projects,I think is like, it's the
manifestation of what everyone,all those like memes or, you
(32:43):
know, very inspiring graphics onmy LinkedIn feed that are like,
you know, be more strategic.
Let's AI elevate you into a morehuman role, yada, yada, yada.
But actually this is likemore than just words.
This is like actuallyokay, this is how it looks.
And especially in the healthcarespace where it is about patient
outcomes and actual, youknow, impacts to livelihood.
(33:03):
I guess the devil's advocatein me, 'cause I think you
touched on it earlier, right?
You're like, there'sstill people wrapping
their heads around this.
It's been a couple years.
These frameworks arerelatively new in the grand
scheme of project management.
But also I think they'redifficult because.
I think the critics wouldsay, well, Pierre's just
trying to turn everyproject manager into like a
strategic C-suite executive.
(33:24):
And yet there's this big gap,right, between learning how
to manage scope, schedule,and budget, and understanding
your industry and the peoplewithin it so well that you
can influence outcomes.
It almost seems likea unfathomable leap.
But of course it'spossible because I do see
people do it every day.
I'm like, what do you thinkthat leap looks like for folks?
(33:44):
Like if you've been leadingprojects in the healthcare
space, but you've had theluxury of being like, I just
make sure things get done,but I don't really have
to engage with outcomes.
How can they then start theirjourney towards the MORE
framework, the where they canthink about outcomes, where
they can think about maximizingthe impact of their projects?
David Doan (34:06):
Yeah, that's a great question.
I think as like amaturity model or curve.
So for example, if someonewho just graduated from the
university, whether they havean MBA or not, and they want
to do project management.
If we wanted to focus onthe project manager role,
first of all, they need toactually know how to project,
(34:26):
manage or manage a project.
What is the methodology?
Whether you are leaningon PMI or you are leaning
on Agile or Scrum, there'sso many variation of that.
So then it takes a fewyears, I think, to really
understand the mechanicsand the methodology of it.
Once you master that.
I think project managersare going to get to a point
(34:46):
where they feel like they cando in the sleep, but that's
always as we know, a triggeror a flag or an alert that
you need to be challenged andyou're not probably learning.
So what we wanted to do is.
You know, project managerone, two, three, or what we
call project coordinator,become project manager to
become program manager,portfolio manager.
(35:08):
So that is an evolutionfor those who aspire to
really think broadly aboutthe impact of how effective
projects are being done.
We'll not just say costand being efficient about
it, but also when you geta product or a service out
sooner, the end users willtake advantage of that and
outcomes will be realized.
(35:30):
And then we also need toreally, I think, take credit
for the things that we do sowell in project management.
Because we need to speak thelanguage of what's the ROI
from many different lens, notjust the quantitative dollar
investment and dollar saveand reduction in readmissions,
or reduction in or increasein revenue because we get
(35:51):
incentivized for doingsomething great in healthcare.
How is that actually goingto make a difference in a
population or a community ora marginalized population?
I think that's a call to actionfor project manager to, I think,
have a pathway to get there.
I don't expect anyone to justchange that mindset, but I
think it needs to be taught.
(36:13):
It needs to be trained.
It needs to have an opportunityfor those who may not already.
A strategic thinker,first of all to have the
opportunity to do this.
And I would say I challengekind of the PMO or the project
manager office organizations andthe leaders of the organization
to really provide the training,but also the opportunity and
(36:35):
all the support to make surethat we think strategically.
'cause that's how you evolveas a leader, whether you're
a project manager or not.
So that's really thechallenge, a call to action.
And I truly believe thatpeople do want to make
connections of what they do.
How is it that isimpacting anyone?
So I do think peopleinherently want to know.
(36:58):
The legacy, that's a strongword to use, but the impact
that they leave behindwhen they successfully
do something, but yeah.
Galen Low (37:06):
That's probably the clearest answer I've ever gotten
to that question, by the way.
Well, what I like about it isthat yes, it is aspirational.
No, nobody expects youto be doing it day one.
It's a maturity model.
You get there.
And also some of the thingsthat we're talking about
project managers are doingevery day and not getting
recognized for it, right?
It's like it's notthat big of a leap.
(37:28):
When you stop thinking aboutproject management as scope,
schedule, budget, you know,measurable dollar outcomes or
KPIs that are fundamentallynot the KPIs, right?
They're just likeindicators, not outcomes.
When you strip that all back,you know, what are we doing?
We're interfacing with humans,we're driving collaboration,
we are aligning viewpoints, weare driving towards outcomes.
(37:50):
So even though it soundslike a big leap on paper.
When you kind of frameit the way you have,
you're like, yeah, no.
It's just like thejourney can continue up.
I love that about the, if youfeel like you can do it in
your sleep, yeah, you probablydo need to get challenged.
And I think the path doesgo higher than what we think
of, you know, we're like,oh, senior project manager,
I guess you've topped out andthen just make some lateral
(38:10):
moves and that's your career.
But actually there'san opportunity to.
I think legacy is a strongword, but not too strong
of a word when you'retalking about projects that
are transforming lives.
And I think that's yeah, that'sa really good way of putting it.
David Doan (38:23):
Yeah.
I would just challenge theproject managers out there
who might be listening.
When you're done with a project,let's say you led an AI project
in healthcare, do you ever goback to the end user that it was
intended for and ask them, howdid the technology work for you?
How do you feel as far astrusting the technology?
Like asking these questions,you get that qualitative kind of
(38:45):
feedback, but you also probablyhear things like, I kind of love
it, but I wish they can do X,Y, Z. So that's really where we
need to make that connectionsto the human users of that.
And I think that is reallysomething we don't do very
well in project management.
We've done awesome.
We check off, I just leta successful project.
(39:06):
I don't know if we ever go backand really have a conversation
with those who are the recipientof these wonderful things that
we built and explore other kindof improvement opportunities.
Galen Low (39:18):
For me, like I'm very guilty of that.
Like, and I came from an agencybackground, so it literally was
that you roll off a project,it's done, you move on to the
next one, you don't look back.
You don't even have achance to look back.
And I know a lot of folks in mycommunity will say that still.
They'll be like, but David,like, I don't have a chance.
Like they put me on anotherproject as I'm not like part
of this core team necessarily.
I get moved aroundwhere I'm needed.
(39:39):
But I also, it strikes methat like in the healthcare
space, I mean, A, it'sjust so visceral and real.
B, you are impactingthe lives of patients
like real human lives.
And there is an opportunity, Ithink in some cases at least.
To revisit that and likeiterate on a project as part
of an initiative, right?
(39:59):
Like it didn't end there.
Right?
It kept going.
We're still evaluating, right?
The outcomes, I guess.
I mean, the other thing thatstrikes me is that I'm like,
healthcare sounds cool.
It sounds serious.
It sounds like hard work.
The stakes are very high, but.
It's a very relatable lens to belike, how did that go for you?
You know?
Now we have this whatevermedical fall prevention device
attached to you, or now thatwe've got the like sort of
(40:21):
ambient listening now that we'vegot, you know, these tools,
like how is this going for you?
Because it matters interms of the way we take
care of populations.
Then I guess the other sideof me is like, I touched
healthcare a little bit inmy past, but like I'm talking
like hospital websites,you know, not like clinical
systems, not like actualsort of patient solutions.
I'm not a medical professional.
(40:43):
I have had no training there.
But for folks listening whofind this interesting, maybe
they're leading projects, butlike in a different industry,
but they want to like actuallymake the shift into healthcare.
Either A, because you know,they're mission aligned, or
B, it just sounds really cool.
For folks who are likelooking to make a pivot into
leading healthcare projects.
What skills or knowledgeshould they be seeking out?
(41:05):
Do they need to becomedoctors and nurses?
Where should they befocusing their training?
Because I think the otherthing you said there in
there was like, yes, it'sabout getting the right
training to be successful.
David Doan (41:17):
Yeah, that's a great question.
And for everyone who listens,the big response or answer
is no, absolutely no.
You do not need to be aclinician of any sort to add
value in any healthcare project.
In fact, I think what isreally needed is more people
who have fresh perspectivesand different industries to
(41:37):
really cross pollinate and beable to not have healthcare
be mystified and be siloedlike it has been in the past.
So as far as what skills areneeded, just merely being a
project manager, you alreadyset yourself up for success
because when you get yourproject management professional,
or PMP certification or thelike, you are actually being
(42:00):
asked to be able to leadproject in any industry.
So that's a given.
The second is really about,I really think about when I
go back to the PMI (42:07):
Next, and the more that I referred to
earlier is about influencepeople and having effective
communications to affect change.
And that requires leadershipskills and that really
apply to any industry.
I think there's an opportunityfor younger cohorts to really
(42:27):
take advantage of the AI anddata literacy and fluency,
because everything we talkabout AI really needs to start
with the foundational datagovernance, data normalization,
standardization, data integrity,you name it, you can just
do a little Google search.
So having to passion to learnmore about data and AI or
(42:47):
this data literacy in generalis an awesome skillset.
We need more people like that.
And then I think that you mightneed to be mindful of certain
industry and healthcare isone that is everyone knows is
highly regulated, just like thefinancial or banking industry
being exposed to learning about.
When I mentioned CMS earlier,or the CDC, everyone have
(43:08):
heard about HIPAA or theFederal drug administration.
I think get more immersed inwhat are some of the regulatory
requirements that has come downthat we all need to be aware of.
Even people who areclinicians are learning
those regs as we speak.
So don't feel like justbecause you're not a clinician,
we are just interpretingit as quickly as the next
(43:29):
person, regardless of ourclinical background or not.
In fact, like CMS-0057,which is the interoperability
and prior authorization,reg, the final rule was
published in a lot of it'stechnology, like I am trying
to understand the technologylens of it, and I think.
Lastly is having somesense of empathy, and that
shouldn't be hard at all.
(43:51):
I think people get intohealthcare is because you
might have a personal storyor you have a loved ones,
whether that's your brother,your sister, your grandparents
that have gone through what Icall the care journey and you
didn't feel like it was ideal.
That is what drives you,and that's the intrinsic
motivation that feed thepurpose, and that is the
passion that comes through.
(44:12):
When you work with any project.
Imagine that gets translatedinto project that you are
leading in healthcare.
It'll become evident thatyou listen for nuances
and you care about who'sactually delivering the care.
So what I think is empathysometimes helps as well,
and it has nothing to dowith being a clinician.
It helps you to be curiouswith a sense of humility
(44:34):
and the ability to translateand make connections from a
technologist, data science toan infrastructure person, to
a QA person, and ultimatelythe various clinicians.
So, no, you do not, and wewelcome speaking on behalf of
my other colleagues to have.
People who are engineer, youknow, engineers and financial
people to really do a lot ofwhat I call the QA to help
(44:58):
us to make sure that we areleveraging the diversity of
thoughts, but also skills.
Galen Low (45:03):
I love that.
I also love that it's likein finding that empathy,
almost everyone has astory of going through some
sort of healthcare journeythemselves or their loved
ones, or someone they know.
And then isn't it so humanto be like, and this part
of it could have been betterand anchoring around that
to drive your curiosityto be like, you know what?
(45:24):
And you know, I know somepeople in my life, you know,
who are very inspiring,who were impacted in some
way by some kind of healthevent or health crisis.
And have taken up themantle to learn, right?
To be like, okay, wellI need to learn as much
about this as I can.
Even if that means me readingmedical journals that I only
kind of understand and justlike using the tools available
(45:44):
to me to get smart about this.
And the same could be truepivoting into healthcare.
It's not like these answersare inscribed on some scroll
that's hidden in a templefar away you can get at it.
The HIPAA stuff, it's like,sure, it's gonna be dense,
it's gonna be a challenge,but it's out there.
And if you're committed to it,then you know you're learning.
And guess what?
Everyone else is learning too.
You're not necessarilythat far behind.
(46:05):
It's those perspectives andthat empathy that really
kind of drives it through.
David Doan (46:09):
Well, summarized Galen.
Galen Low (46:10):
Well, well said for in the first place.
This has been a lot of fun.
I know we could go on for days.
I'd love to have youback to talk about
measurable health outcomes.
But maybe to wrap it up,just for fun, do you have a
question you wanna ask me?
David Doan (46:26):
Oh my gosh.
I was waiting for thisopportunity 'cause I
wanna learn from you too.
I would say that for someonewho knows project management
well and interact and learn fromother project leaders week after
week in different industries.
I would say what would be kindof the big trend out there or
the shift in mindset of thinkingwhen you're seeing like digital
(46:49):
projects outside of healthcare,what can be taken from someone
who is so deeply immersed inhealthcare that it's almost
like project management lessonfor healthcare practitioner to
learn from other industries.
Galen Low (47:05):
I mean, I think it probably happens more in
healthcare than I assume,but I would say like this
sort of cross training,cross pollination between
strange roles that don'tnecessarily talk to one another.
So let me kind ofzoom out from there.
What we're finding sometimes ina good way and sometimes in a
bad way, but digital teams areexpected to do more with less.
Maybe that's true acrossthe board, but in other
words, we see a lot oflike role hybridization.
(47:28):
You know, you're responsiblefor this and this.
You're a business analyst andyou're a project manager, or
you're an account manager andyou're in business development.
And so there's is sortof like collapsing.
And then the other thingwe're seeing is that we're
at like different roles arecoming into the mix because.
This is, I'm dating backof ways, but on a project
I was working on a whileback, we were working with
someone who was a linguist.
'cause we were doing naturallanguage processing on customer
(47:49):
data and customer feedback.
And it was just like thesecollisions of people who
know different things.
And they don't look likethey should fit together.
But if everyone can kindof start seeing from their
perspective and learningfrom one another, then
it can like diversify theway we think of a team.
And like, I think that inany industry we get fixated
on like, what people dowe need to do X or Y.
(48:11):
And we're like, oh yeah, A, B,C. It's like always this team.
We can actually switch itup a lot more to get some of
these different perspectives.
We can intentionallylearn from one another.
And then I think along theway, for better or for worse,
I think we'll be able todo more than just one job.
And that might be an assetactually in like the age of
AI remains to be seen though,because right now it looks
like cost cutting and leanbudgets and employers trying
(48:34):
to get more from their talents.
I think there's an optimisticupside as well from all of this,
which is I think it does sortof level us up and get us used
to working with different peopleand getting us thinking about
things a little bit differently.
David Doan (48:45):
That was very useful, Galen, really.
You know, I'm on top ofit, so I need to make sure
I remember what you sharebecause healthcare can benefit
from implementing just that.
Absolutely.
I know we talk a lot.
I hope that some of thisanswers start with your
curiosity and others as well.
Galen Low (49:04):
Oh, absolutely.
David Doan (49:04):
But it is been a delightful just to just
share, you know, bouncing backquestions and answer responses.
So I learned quite a bit.
Galen Low (49:12):
Ditto here.
This has been a reallygreat conversation.
Thank you again for your time.
Just for folks who arelistening, where can
people learn more aboutyou and what you do?
David Doan (49:21):
I'm relatively active on LinkedIn, so
I really invite peopleto connect with me.
And, you know, for thelast month or so I've been
inspired to write my LinkedInblog, so by the time this
even gets published, Iwill likely have a blog.
And my blog is really arounda handful of topics that I'm
very passionate about to showkind of my multidimensional,
kind of authentic self.
(49:41):
It's not just about healthcareand technology, which I'm
deeply passionate about.
It has taken me so many yearsof making sure that technology
should enable, you know,what the business user need.
Like the strategy should notbe driven by technology only.
It should be drivenby the business and
the clinical leaders.
The other thing I'm passionateabout is I mentioned
health equity a lot.
(50:02):
It's not just because it's oneof the five quintuple aims is
obviously I'm an Asian person.
You know, I'm not just anAsian leader or anything like
that, is I have my own personalexperience with health and
I truly see it with my momand my grandparents as far as
how their care journeys is.
So I think the discussionand the opportunities now,
(50:22):
health equity is importantfor me to highlight.
You know that I'm a passionateadvocate for project
management in general.
That's why I definitely havevolunteered for many years.
But how do we bring the projectmanagement lens to everything?
But it is more strategic projectmanagement and my nonprofit,
(50:43):
it is a lot of synergies whereI think there's about giving
back and putting it forward.
It is not just bringinga team along, but how do
you see the community?
And the community can be definedas your local city or county,
but sometime our communityis global in some ways.
So I think all theseare topics that I invite
people to come read moreabout on my LinkedIn blog.
Galen Low (51:05):
That's super cool.
I like that the blog is whereit kind of all comes together.
I'm super interested to tune in.
I will include links toyour LinkedIn and your
blog when this goes live.
I'm super excited.
David, thank you again.
David Doan (51:17):
My pleasure.
Thanks so much, Galenfor the conversation.
Galen Low (51:21):
That's it for today's episode of The Digital
Project Manager podcast.
If you enjoyed thisconversation, make sure
to subscribe whereveryou're listening.
And if you want even moretactical insights, case studies
and playbooks, head on over tothedigitalprojectmanager.com.
Until next time,thanks for listening.
What role do project leaders play in
(00:03):
building this trust withinAI healthcare projects?
David Doan (00:06):
Project managers are not just task master.
They should be framing anAI project as not just a
technology deliverable, butit's a human-centered change.
It's integrating thattechnology with what I call
humanizing the AI project.
Galen Low (00:20):
Why is it so important that healthcare
finds ways to adopt AI?
David Doan (00:24):
What is that stake ultimately is more than
efficiency and effectiveness.
This has a directimpact to patient care.
If that adoption fail, there'sa grave risk of patients
may miss out on potentiallife saving interventions.
There may be misdiagnosis ifthe predictive of modeling
does not make sense,especially if AI models are
(00:47):
trained on incomplete data.
Therefore, the marginalizedpopulation may face
worse health outcomes.
Galen Low (00:54):
Healthcare is so interesting because
it's that rigor by default.
It has that many stakeholderswith that many different
perspectives, and so it's almostone of the most complex versions
of the game of implementing AIto create solutions that drive
better outcomes for humans.
(01:15):
Welcome to The Digital ProjectManager podcast — the show that
helps delivery leaders worksmarter, deliver faster, and
lead better in the age of AI.
I'm Galen, and every week wedive into real world strategies,
new tools, proven frameworks,and the occasional war story
from the project front lines.
Whether you're steeringmassive transformation
projects, wrangling AIworkflows, or just trying to
(01:36):
keep the chaos under control,you're in the right place.
Let's get into it.
Okay, today we are talkingabout the immense potential
of AI in healthcare and whatproject leaders can do to build
trust, raise risks, championethics, and ultimately drive
patient outcomes through AIpowered healthcare projects.
(01:56):
My guest today is DavidDoan, Director, Consult
Partner for Healthcare& Government at Kyndryl.
David is a healthcaretechnology and business
transformation leader withover 30 years of clinical
and consulting experience.
He started his career at thebedside as a registered nurse
for the first 10 years andthen went on to consult at
McKesson, Accenture, Ernst& Young, and is now partnering
(02:19):
with C-Level and IT executiveclients to drive strategic
digital transformation, AIinnovation, and value-based
care initiatives at Kyndryl.
Beyond that, David is thepresident of PMI Los Angeles
chapter, serves on the boardof directors of five other
nonprofit organizations, is amentor for the Asian American
Professional Association,and so far that's only
(02:40):
half of his rap sheet ofaccolade and accomplishments.
It's very impressive, David.
Thank you for being on the show.
David Doan (02:46):
My pleasure, Galen.
Absolutely.
Galen Low (02:49):
I know we zig and zag and like as we
were preparing for this,we covered a lot of ground.
For this episode, I'm hopingthat we can just cover just
the excitement and the fearsurrounding AI enhanced
patient care and what canbe done to address both.
Maybe just like what's at stakefor our healthcare industry
if we don't get AI, right?
How a framework of trust canhelp project leaders align
(03:12):
disparate stakeholder groups.
And maybe just how projectleaders would know previous
healthcare experience canget into the healthcare
space and maybe vice versa.
How does that sound to you?
David Doan (03:23):
That's wonderful.
Great discussions,great questions.
I have my work cut out, butI'm pretty sure I can provide
a little bit of insightbased on my experience.
But yeah.
Great discussion.
Galen Low (03:34):
Well, if I learned anything about you so far,
it's that you're fast on yourfeet and you know your stuff.
So I'm gonna challenge you.
I'm gonna challenge you.
We've got this tradition herewhere I kind of start with
like the big question, theone hot question that we can
then sort of zoom out from andthen build the context around.
So my big question is this,what is the biggest fear
(03:54):
that clinicians and medicalpractitioners have when it comes
to AI being introduced intothe way that they deliver care?
David Doan (04:01):
Yeah, great questions.
Very relevant one.
I summarized it inkind of two topics.
One is the fear of losing humanconnection and judgment is one.
So I touched on that.
And the second is reallythe fear of accountability.
So I actually started mynursing career writing.
(04:22):
Literally writing, you know,there's no such thing as an
electronic health record orelectronic medical record.
And when we move intotechnology, even just giving
medications out of thismachine called Pyxis Machine,
we always were fearful of howis that going to disconnect
us with the patient somehow.
AI is definitely anotherexample of advanced technology
(04:44):
that can actually do that.
So for example, now there's a AItool, machines and predictive,
you know, machines that canactually read the film from
a chest x-ray or a PET scan.
So there's that fear of notbeing able to actually, you
know, touch and feel and havingthat human connection and
also the judgment as you know,you know, medicine, nursing.
(05:07):
It's certainly a science,but it's a lot of art and
that requires a lot of data,clinical data, nonclinical
data, and in the last pieceof the puzzle in healthcare is
really the clinical judgment.
That's really what differentiatebetween a nonclinical staff
versus a clinician that has,you know, a license that they
need to practice at the top ofthe license, but also a sense
(05:29):
of accountability as well.
So I think that the fearwhere AI can actually replace
conversations and dialogues withpatients at the bedside, or even
when you adopt visiting a doctorvisits or even sometime when you
have telehealth or telemedicine,is that they fear that they
cannot and should not lose.
Really the clinical judgmentand their decision making.
(05:52):
So whatever technology ortool, that is one thing that
we need to really address andit needs to be collaborative
with the clinicians.
So algorithm thatspit out predictions.
They need to make sure thatthe data is insightful at
the point of care, but reallyappreciate the need for the
clinician to understand andtrust the data and the insight,
(06:14):
but really preserve thatsacred clinicians and patient
relationships, so that waythey're still somehow providing
data, clinical judgments thathelp inform the decision making.
The accountability piece isimportant too because you
know in medicine, cliniciansare trained to do no harm.
We wanted to make sure thatthe AI or technology model
(06:36):
actually works, and thatway it makes recommendations
that it is consistent,aligned with evidence-based
guidelines and all of theother reputable professional
organizations recommendations.
That accountability reallyrests on, can clinicians
still have that final reviewto make sure that they still
ultimately accountable forit, but the AI system, or the
(06:58):
technology and the engineeraround that, there has to be
some due diligence to ensurethat data is not false, to
help ensure that trust as well.
That's a little bit long-winded,but I would say two really
fears that if you break itdown, is really about the human
connections or making sure thatthere's no loss of that, and
that also the clinical judgment.
(07:20):
And second is the roleof accountability of a
clinician, but also fromthe technology side.
Galen Low (07:26):
I love that and like I like that you framed
it around the fact that it'slike an art and a science.
Right.
And I think sometimes it'seasy to get swept up from
a very high level of, oh,it's just information.
We can upload all of ourmedical knowledge and then that
information will be available.
But I also like the otherthing you did there, which
I don't know if you meantto do it, but there have
been a lot of disruptivetechnological progressions
(07:49):
in the healthcare industry.
You mentioned some ofthe prescription apps.
We're talking about telehealth.
There's been a lot ofthings, and I think.
What I like about youranswer there is that these
are the underpinningsthat have helped us get
through all of this change.
And I know like EHR, like theelectronic health records or
electronic medical records, it'sbeen a long journey, hasn't it?
(08:10):
Right.
At my time in consulting,we're still transitioning
systems over.
In some ways.
It's not justtechnological progress.
It's like we're still buildingtrust and we're still being
careful because of that oath,because we can't just assume
that something that happens ina black box is gonna work well
every time or 90% of the time.
(08:30):
Like that isn'tquite good enough.
It's the judgment andit's the sort of humanity
that needs to stay in it.
I think it's fascinating.
And then also I just thinkthat idea of the consistency,
you mentioned consistency, andimmediately my head went, oh
yeah, hallucinations in AI.
It's fine in my work, right?
It's like, wait, hold on.
(08:50):
That was not the answerthat I was looking for.
Or even I asked it the samequestion three times and
got three different answers.
That's fine, I can fix that.
But like when it comes topatient care, that is something
that we have to do very Right.
And I'd be very carefulabout, so I know that's
all the Right, yeah.
Important things.
But I wondered if maybe we couldzoom out a little bit because.
(09:13):
We've been talking a littlebit about accountability and
trust, the patient experienceand the humanity of it.
We talked a little bit alongthe way about sort of some
technologies and technologyalways does find its way into
healthcare for good reasons.
AI seems a little bit differentin some ways, or maybe it's
not, but I thought maybe I'djust kind of ask why is it
so important that healthcarefinds ways to adopt AI?
(09:35):
What's at stake here and what'slike the biggest barrier that
AI adoption faces in healthcare?
David Doan (09:41):
What is at stake ultimately is more than
efficiency and effectivenessof how clinicians interact
with their member or patient orthe healthcare delivery team.
'cause there's a whole teamthat managed the patient is
ultimately, really result topositive or health outcomes.
(10:03):
So there is suchbig ramification
and consequences andconsideration to think about.
It's not just makingsomeone's workflow easier,
having a better experience.
Ultimately this has a directimpact to patient care.
And then that patient care,even though it's one-on-one
with the practitioner at a time,it actually ultimately results
(10:25):
in what I call on a massivescale called population health.
And it also aligns with.
The quintuple aim, where it'snot just about costs, it's not
just about access, it's nowabout the clinician experience,
the patient experience.
And finally, at the tip,which is the fifth kind
of layer of this kind oftriangle is health equity.
(10:49):
So where does AI come into that?
AI can definitely, certainlypredict the diseases taking
in so much data, the clinicaldata, the claims data, the
nonclinical data, the publiclyavailable data and so on.
All of that helps to predictwhich patient cohort or
populations that the providersor the health plan or payer
(11:11):
can identify quickly tointervene to kind of slow the
progression of any diseasestate chronic conditions.
Now if that adoption fail,what you can see is there
are patients that should bemanaged and they're not, or
they have been identified ofhaving something that they are
not they're not appropriate.
(11:31):
There's also an opportunitywhere there's a grave risk
of patients and membersmay miss out on potential
lifesaving interventions.
There may be misdiagnosis ifthe machine or the modeling
tool does not make sense.
And when we think abouttechnology, there's also a lot
of people who don't live inlarge metropolitan cities, in
(11:53):
rural populations where there'scritically accessed hospitals.
We are still beingchallenged with technology.
The technology may be available,but the 5G connection and
network connection, theinternet connection, or how
do we actually manage that?
And when I talkabout health equity.
Are you expecting someonewho English may be their,
not their first language,but they also are challenged
(12:15):
because of dexterity, levelof education or age and so
on to be able to use whatevertelehealth medicine it is?
So when you talk about AI,there's a huge implication
in what's at stake isultimately the health
outcomes of the population.
The biggest barrier, I kindof alluded to it, is a lot
of it is there's technologybarrier from the receiving
(12:39):
of the receiver of carethat's your patient's member.
But if I were to focuson the clinicians and the
care deliverer and also thecaregivers, is that really
that trust we talk about?
But from a technology side,information needs to be
interfaced or integrated andimmersed into the workflow.
So if it's not immersed inthe workflow, AI may force
(13:02):
the clinician to use anothertechnology, or you have to
have a little thing thatto record the conversation.
Where does that information go?
Does it actually immerseor present it in what
I call the naturalworkflow of the clinician?
Because if it does not presentitself in that workflow,
that is really seamless.
It's not gonna increase theadoption of the usage of
(13:26):
the whatever the technologyis, because anything that
disrupts the clinician timewith patients that will
result in poor adoption.
And lastly, you know,there are biases.
So if AI models are trainedon like incomplete, you know,
lack of data or the data isnot normalized, standardized,
or skew in some way, thereforethose are the opportunity
(13:50):
where patients could.
Especially the marginalizedpopulation may even face
worse health outcomes.
So that's what's at stake ismassive about health outcomes
and then also the adoption ofclinicians with technology.
Galen Low (14:06):
I'm really glad you went there, especially
with the patient andclinician experience.
My background's in user-centereddesign, so like mostly we're
like digital solutions that.
Yes.
You know, solve a problem,make something more
efficient, leverage moredata, but also fundamentally,
yeah, have to be workable.
Have to enter into a workflowseamlessly so that it doesn't
(14:27):
create an additional barrier.
And you were saying up top whenyou were a registered nurse,
you're doing bedside care.
You know, you're writingthese things by hand.
And there is an opportunityto really give some of that
time back right to a medicalpractitioner so that they
can focus on patient care.
At the same time, not addinglike an additional step in there
(14:49):
that might actually lead toworse outcomes or lead to more
challenges in delivering care.
And that health equity thing,I hadn't really thought of
it in that way, but like Iwas chatting with someone
last week, we were talkingabout how AI is sort of, it
kinda like levels the playingfield in some areas, right?
Where right now there's peoplewho are vibe coding, they've
never been developers before.
(15:10):
They didn't train to be adeveloper, but now they're
able to create an applicationand vice versa, right?
Technical folks who weren'ttaught or don't consider
themselves well versed inlike business language now
can sort of use some ofthese tools available to
them to sort of have thoseconversations and like break
down some of the silos.
And I did a little bit ofwork in like outpatient
(15:32):
care, telehealth sort ofstuff from a digital side.
And it really opened my eyes.
I think you, what you said aboutfolks living in metropolitan
areas versus bulk of thepopulation, which doesn't, you
know, we're scattered about.
The infrastructure is different.
The United States in particularhas been pretty aggressive about
getting broadband everywhereand the 5G transformation.
(15:54):
But it's still not everywhere.
We can't just assumethat everyone has access
to all these things.
Has the ability to engage withall these things is open to
all of these things, and Ithink that's the big zoom out.
Why I think it's superinteresting in the healthcare
side of things, because unlikesome of the things that we
talk about in the businessworld where we're like.
Hey, we can get copilot,you know, to be helping
(16:16):
us write documents.
We're all sort of a certaintype of knowledge worker
doing a certain type of job.
Healthcare is not that.
Healthcare iseverybody, you know?
It impacts everybody.
It goes across demographics,it goes across, yeah, a lot of
different things, and that's whyI think it's such an interesting
and juicy topic because evenif you're not in healthcare,
if you're listening to thisand you're not in healthcare.
This at least shows thatpicture of AI at scale, right?
David Doan (16:39):
Absolutely.
Galen Low (16:40):
With different members of the population
for something that reallymatters, which is the health
of our population, patientoutcomes, and ultimately health.
I did like also what yousaid about preventative.
It kind of got me thinking,you know, predictive
analytics, right?
It's one of those thingsthat, you know, a lot of
businesses are like, yeah,they've been on it for years,
so that they can anticipate.
And then I start thinkingabout things like.
You have your health spendingaccount to get like an
(17:02):
ergonomic office chair.
In some ways, that'spreventative care because
it's like, okay, if you'renot sitting in a garbage chair
all the time, then you're notlikely to develop back pain,
chronic back pain that then weneed to treat in a certain way.
And then I started thinkingabout strain on system and
I'm like, okay, well thereare health administrators,
healthcare leaders, and evenjust the business side of the
(17:22):
system going, wow, that's great.
Yes, we wanna prevent.
Some of these thingsfrom getting too far.
You said, you know, interventionat the right time to get
people the care that they need.
And I'm also like, well, someof the folks, don't get me
wrong, noble in intention aswell, but it's their job to
also think about strain onsystem and like money, right?
To be like, well, it gets alot more expensive to treat
(17:43):
people later in their healthjourney, whereas if we catch it
early, that could be cheaper.
Then it got me thinking, becauseyou actually are someone who
did a decade at bedside asa registered nurse before
entering the consulting world,and now you work with chief
medical officers, you workwith regulators, you work with
other decision makers in thehealthcare space, but in other
(18:06):
words, like you actually aresomeone who can see things
from all the perspectives.
It got me thinking about liketrust, but also how can trust
around AI be built betweenpatients and caregivers and
clinicians and regulatorsand business leaders.
They all look at it froma bit of a different
perspective and like what'sinvolved in reconciling
all those perspectives.
David Doan (18:26):
Yeah.
You are making mework very hard.
But Galen I'm delightedto share my perspective
on the hard question.
You know, just by youlisting all of those names
of what I call stakeholders.
So in healthcare,it's never a person.
It's always what I calla healthcare ecosystem.
And that ecosystem may be peoplethat are likely invisible to
(18:48):
the patients or the members.
Like for example, youmentioned about regulators.
So there's accrediting bodies.
There's also centers forMedicare and Medicaid services,
or CMS and the Center forDisease Control, et cetera.
They want governance andthey wanna make sure that
ultimately the care that isbeing delivered, whether you
use advanced technology or notechnology, is actually, you
(19:11):
know, quality and is safe.
And you also have thepatients who want reassurance.
Reassurance that you providepractitioners or doctors.
Even know about the culturethat I am raised up or the
language that I speak, becausethat has a lot to do with the
type of food and nutritionsthat I have a preference on.
(19:31):
Obviously clinicianswant to see evidence.
They are trained toreally review what we
call peer review articles.
It's not just word of mouththat, oh, the CIO or the
chief digital officer ordata officer said that we
need to adapt ambiance.
You know, listening AI,that's great, but what's the
evidence as far as has therebeen done any research that
(19:54):
shows actually there is a highprobability that is correct
versus how do we address.
Some of the hallucinations, youknow, we'll be talking about
AI or just really misdiagnosis.
So that's reassurance.
Like, I don't want tobe the first hospital
to do this, or the firsthealth plan to do this.
Has there been any evidence?
When we say evidence, it's notjust a blog, it's peer review
(20:16):
articles, and that takes time toreally build that literature up.
And then you said businessleader, I hate to say
it, it's really aboutfinancial performance.
Even in a hospitalsetting, it is a business.
So they want to see hard,quantifiable, ROI with
these very expensiveadvanced technology.
So let me just give you somesuggestions of how to bridge
(20:37):
that gap to ensure transparencyand having that shared
language to really build trust.
Because we talk about, yeah,those are the problems.
Those are the backgroundthat we have to work off of.
One is what I callexplainability.
How do you actually havethe data to really think
about in plain language?
Make the connection from atechnologist, from an engineer,
(20:58):
from a data scientist, froma product manager talk to
a clinician to say theyunderstand the business problems
and also the opportunities,meaning the specific use
cases that AI can be applied.
Can you explainhow it will help?
Can you explain how AI works?
The X, Y, Z data.
So if they understand it,you're gonna be able to get
(21:20):
buy-in, but also allow that,what I call the collaboration,
to have the clinician orthe business leaders to ask
questions because they areso busy, they don't know the
details behind the technology.
You have to talk about safeguardwith information, with data.
We have to talk about theconnectivity of multiple
data, how it gets presentedinto the workflow at what
(21:43):
I call the point of care.
Being able to explain that inlay language or playing language
on both sides, because theclinicians may be presenting
a very specific use casethat the technologist may not
understand fully what that is.
The second is really inclusionin design is you mentioned
that you have background userinterface, user experience.
(22:05):
Well, you have to have thevoice of the customers.
So who are these customers?
The patients, the nurses,the practitioner, but also
could be physical therapist,the pharmacist, everyone
and everyone else you needto really consider just
because you're a clinician,a pharmacist workflow, as
you may already know, isvery different than a nurse,
than a physicians, et cetera.
(22:26):
So those are the thingsto be considered.
The modules within an EHR isconfigured differently for
different floor and differentunit, be as inclusive in the
design and the implementationand the change management.
And then it needs to reallybe couched around governance.
People are rushed intoimplementing AI without
(22:47):
solid policies, withoutthe framework, without
the governance structure.
I know everyone talkabout framework.
Everyone has a framework ineverything, consulting firm,
but we need to carry that out.
What are some of the safeguardor the guardrails around.
Equity, fairness, bias,privacy, accountability
that we need to address.
I know that's kind of boringstuff, but without that,
(23:09):
you will not be successfulin rolling out and the
adoptions will not be there.
And also this risk on kindof the regulatory side.
And lastly is thecultural storytelling.
What is this all about?
It seems like itdoesn't fit, does it?
So how does AI improve not justthe numbers, the quantifiable
ROI, but actually patient lives?
(23:30):
Let me give you an example.
Those clients that I am ableto have the privilege of
working who I think got itright, is that they actually
tell the technology team thatwhatever you're building or
the requirements that youare writing and that you are
testing, if you don't understandhow this is used by clinician
X or business user X and howthat ultimately mapped to the
(23:54):
positive experience and healthoutcome of the patients, then
they should have no businessworking on this project.
Brilliant.
The technology team shouldbe an extension of the
clinicians or the caregiver,so they should be actually
caregivers of the caregivers.
So that is when Ithink trust is built.
So without that trust throughtechnology, you don't have
(24:16):
really the people, theprocess in place and buy-in.
So I think storytellingis about the voice of the
customer through conversation,through collaboration that
you buy-in and that willhelp with transparency and
therefore trust will be enabled.
Galen Low (24:32):
I love how that kind of.
You paint it out as anecosystem, and I think a
lot of people understandit as an ecosystem with a
lot of stakeholders in itthat you know for a cause
that really matters, right?
People's healths and livelihood.
But I love that notion oflike even like the product
team, the tech team being thecaregivers of the caregivers,
and it's all actually this.
It's one picture that differentstakeholders have to look
(24:53):
at it from different lensesthrough different lenses from
different angles, like yourchief medical officer or you
know, those are sort of businesslens on things like, yeah,
they have to care about money.
'cause guess how patientcare is delivered, right?
It requires funding, itrequires money and also.
It is something that islike very regulated, right?
We have these things in placeand it's funny, I like sort of
(25:16):
drawing the comparison to, forexample, the business world and
you and I, we both come fromthe consulting world, so I think
we can say this, but it's everyother week that BCG, McKinsey,
Accenture, EY, the publishinga report, everyone's sharing it
on social media or via email.
We're going, oh,that's a good idea.
Let's start doing thatright away versus like.
(25:36):
Has it been in a purereviewed journal?
Right.
You mentioned things likeambient AI listening, right.
And then I'm like, I haven'tbeen very close to a sort
of medical journal recently,but like what an interesting
way to sort of vet out theseideas at like the highest
rigor of very smart peoplewho understand the technology
(25:58):
and the health implicationsand the human implications.
Being critical of one anotherto sort of make sure that
this is the right thing,not just a thing we can try.
It's a completely differentpicture than how a lot
of people think about AI.
Even folks listening.
And maybe a bit of partof me is like, well,
shouldn't it be easy?
Just try and roll out alittle pilot program and
(26:18):
then scale from there.
Like, you know, be iterative.
Isn't that what we always do?
No, unfortunately, the CDCalso has to be on board, so
you kind of have to have.
David Doan (26:25):
That's right.
Galen Low (26:25):
It's a whole different thing.
But I do also think thateveryone can take a page
outta this book, right?
It's almost this like macroview of where we're heading.
We started out with AI inthe sort of business world,
in less regulated areas,just like trying stuff.
Then we're gonna run intothat governance wall, right?
We're gonna run into the dataquality wall, we're gonna
run into all these thingsthat sound boring to us now.
(26:46):
But are gonna matter foreveryone pretty soon.
And that's why I thinkhealthcare is so interesting
because it's that by default,it's that rigor by default, and
it has that many stakeholderswith that many different
perspectives by default.
And so it's almost like oneof the most complex versions
of the game of implementingAI to create solutions.
(27:07):
That drive betteroutcomes for humans.
It's really interesting.
I love that sort of framework.
I wonder if I can bringit back to the sort of
the project level as well.
I recognize you and Iwere passionate about
this sort of stuff.
Like we can talk ata very high level.
You know, we've beentalking about trust and I
kind of frame this around.
AI powered or AI relatedhealthcare projects, whether
(27:29):
that's implementing AItechnology or using it in the
project, but it is, it stillcomes back down to trust.
It's, you know, it'squite a complex picture.
What role do project leadersplay in building that trust?
Like is there a responsibilityfor folks who are delivering
some of these projects andjust like you said about.
The technologists being thecaregivers for the caregivers,
you know, what role doesa project manager play in
(27:52):
building this trust withinAI healthcare projects?
David Doan (27:56):
Well, this is a question that I'm passionate
about just because of ourkind of connection with
project management in general.
As you introduced me, I'mthe president of our Project
Management Institute of PMI, LosAngeles chapter, so I definitely
wanted to highlight some ofthe PMI concept and methodology
here in the framework as well.
(28:16):
But as far as the role ofproject managers in building
trust, project managersstrategically has been
able to orchestrate all ofthe stakeholders and all
the project team members.
So they are at a veryprivileged, critical role of
being able to see from alland all aspects, I would say
project leaders need to first bestrategic, but also be able to.
(28:41):
Make the translation so that waythe clinical, the business and
all of the stakeholders kind ofunderstand one another because
that is really important that wespeak, quote the same language.
Why would say, not justspeak, but really to
understand each other kindof needs and intentions and
requirements and all that.
And then by being thisphysician of quarterbacking.
(29:02):
You want to be able to thenfreely and proactively raise
risk early and transparently,and think of framing an
AI project as not just atechnology deliverable, but
it's a human centered change.
It's integrating that technologywith what I call humanizing
the AI project where weare reminding project team
members that is ultimatelyfor healthcare anyway.
(29:24):
I'm speaking from a healthcareindustry perspective, is
that whatever is beingintroduced that is ultimately
going to hopefully increaseproductivity, that yield
more what I call FaceTimewith the patients or members.
And that somehow wouldresult in kind of a
positive health outcomes.
I think it's all about outcomes.
That could be a whole topicof discussion, is how to even
(29:47):
measure health outcomes andwhat are the vehicles and
the data that will be needed.
So back to project management.
I have been an advocate ofproject managers on not just
task master, and we are nothere to just tell people when
to do things and how to dothings and all that, because
you can have a robot doing that.
(30:08):
I think project managers arenot being tapped into the
visionary, strategic problem,critical thinking skills.
Let me give an example.
I'm gonna reference president ofPMI, Pierre Le Manh, and he and
his team introduced a conceptcalled PMI:Next, and that was
probably about two years ago.
And I think chapters andproject leaders are still trying
(30:30):
to understand what that is.
So to me, how I interpretthat is really the vision
of what PMI or projectmanagement in general.
So what is that vision?
So we tend to say that thevision is really about.
The purpose of what it is thatwe are doing to elevate the
project success that enablessome sort of transformative
(30:51):
change in the world.
It needs to rely on strategy,being able to not just deliver
the value of tools, butenable continuous learning.
There's also kind of theculture values and then the
framework that helps supportthat vision or executing that
vision is what PMI call it MORE.
It's an acronym, MORE,which is really maximizing
(31:15):
the success through notjust traditional metrics.
We are very familiarwith what I call scope,
budget, and schedule.
But what is really the outcomeor the positive impact in
healthcare that will bepositive health outcomes?
Are we actually saving lives?
Are we actually increasingthe longevity of how patients
live, not just in number ofyears, but the quality of their
(31:39):
experiences in how they live?
Are they actuallychanging behaviors?
Those are positivehealth outcomes.
How do we organize theimpact by empowering our
professionals to reallybuild a stronger community?
And how do we reinventand reengage the
ecosystem of stakeholders?
So all these things are soimportant as what the role of
a project leaders or managershave in any project, but
(32:01):
particularly in healthcareenabling AI is really
adopting that kind of mindsetof PMI:Next and PMI MORE.
So that is the role.
A very important role of astrategic project manager has
in leading projects technologyproject in healthcare.
Galen Low (32:20):
I love that.
I love the tie in withbeing the translator, the
translating quarterback,and how it ties into like
your explainability, right?
Like there's a veryhuman element there.
Even just the fact that yousaid that like these are.
Projects that are about humans,like we need to actually
humanize technology projects,I think is like, it's the
manifestation of what everyone,all those like memes or, you
(32:43):
know, very inspiring graphics onmy LinkedIn feed that are like,
you know, be more strategic.
Let's AI elevate you into a morehuman role, yada, yada, yada.
But actually this is likemore than just words.
This is like actuallyokay, this is how it looks.
And especially in the healthcarespace where it is about patient
outcomes and actual, youknow, impacts to livelihood.
(33:03):
I guess the devil's advocatein me, 'cause I think you
touched on it earlier, right?
You're like, there'sstill people wrapping
their heads around this.
It's been a couple years.
These frameworks arerelatively new in the grand
scheme of project management.
But also I think they'redifficult because.
I think the critics wouldsay, well, Pierre's just
trying to turn everyproject manager into like a
strategic C-suite executive.
(33:24):
And yet there's this big gap,right, between learning how
to manage scope, schedule,and budget, and understanding
your industry and the peoplewithin it so well that you
can influence outcomes.
It almost seems likea unfathomable leap.
But of course it'spossible because I do see
people do it every day.
I'm like, what do you thinkthat leap looks like for folks?
(33:44):
Like if you've been leadingprojects in the healthcare
space, but you've had theluxury of being like, I just
make sure things get done,but I don't really have
to engage with outcomes.
How can they then start theirjourney towards the MORE
framework, the where they canthink about outcomes, where
they can think about maximizingthe impact of their projects?
David Doan (34:06):
Yeah, that's a great question.
I think as like amaturity model or curve.
So for example, if someonewho just graduated from the
university, whether they havean MBA or not, and they want
to do project management.
If we wanted to focus onthe project manager role,
first of all, they need toactually know how to project,
(34:26):
manage or manage a project.
What is the methodology?
Whether you are leaningon PMI or you are leaning
on Agile or Scrum, there'sso many variation of that.
So then it takes a fewyears, I think, to really
understand the mechanicsand the methodology of it.
Once you master that.
I think project managersare going to get to a point
(34:46):
where they feel like they cando in the sleep, but that's
always as we know, a triggeror a flag or an alert that
you need to be challenged andyou're not probably learning.
So what we wanted to do is.
You know, project managerone, two, three, or what we
call project coordinator,become project manager to
become program manager,portfolio manager.
(35:08):
So that is an evolutionfor those who aspire to
really think broadly aboutthe impact of how effective
projects are being done.
We'll not just say costand being efficient about
it, but also when you geta product or a service out
sooner, the end users willtake advantage of that and
outcomes will be realized.
(35:30):
And then we also need toreally, I think, take credit
for the things that we do sowell in project management.
Because we need to speak thelanguage of what's the ROI
from many different lens, notjust the quantitative dollar
investment and dollar saveand reduction in readmissions,
or reduction in or increasein revenue because we get
(35:51):
incentivized for doingsomething great in healthcare.
How is that actually goingto make a difference in a
population or a community ora marginalized population?
I think that's a call to actionfor project manager to, I think,
have a pathway to get there.
I don't expect anyone to justchange that mindset, but I
think it needs to be taught.
(36:13):
It needs to be trained.
It needs to have an opportunityfor those who may not already.
A strategic thinker,first of all to have the
opportunity to do this.
And I would say I challengekind of the PMO or the project
manager office organizations andthe leaders of the organization
to really provide the training,but also the opportunity and
(36:35):
all the support to make surethat we think strategically.
'cause that's how you evolveas a leader, whether you're
a project manager or not.
So that's really thechallenge, a call to action.
And I truly believe thatpeople do want to make
connections of what they do.
How is it that isimpacting anyone?
So I do think peopleinherently want to know.
(36:58):
The legacy, that's a strongword to use, but the impact
that they leave behindwhen they successfully
do something, but yeah.
Galen Low (37:06):
That's probably the clearest answer I've ever gotten
to that question, by the way.
Well, what I like about it isthat yes, it is aspirational.
No, nobody expects youto be doing it day one.
It's a maturity model.
You get there.
And also some of the thingsthat we're talking about
project managers are doingevery day and not getting
recognized for it, right?
It's like it's notthat big of a leap.
(37:28):
When you stop thinking aboutproject management as scope,
schedule, budget, you know,measurable dollar outcomes or
KPIs that are fundamentallynot the KPIs, right?
They're just likeindicators, not outcomes.
When you strip that all back,you know, what are we doing?
We're interfacing with humans,we're driving collaboration,
we are aligning viewpoints, weare driving towards outcomes.
(37:50):
So even though it soundslike a big leap on paper.
When you kind of frameit the way you have,
you're like, yeah, no.
It's just like thejourney can continue up.
I love that about the, if youfeel like you can do it in
your sleep, yeah, you probablydo need to get challenged.
And I think the path doesgo higher than what we think
of, you know, we're like,oh, senior project manager,
I guess you've topped out andthen just make some lateral
(38:10):
moves and that's your career.
But actually there'san opportunity to.
I think legacy is a strongword, but not too strong
of a word when you'retalking about projects that
are transforming lives.
And I think that's yeah, that'sa really good way of putting it.
David Doan (38:23):
Yeah.
I would just challenge theproject managers out there
who might be listening.
When you're done with a project,let's say you led an AI project
in healthcare, do you ever goback to the end user that it was
intended for and ask them, howdid the technology work for you?
How do you feel as far astrusting the technology?
Like asking these questions,you get that qualitative kind of
(38:45):
feedback, but you also probablyhear things like, I kind of love
it, but I wish they can do X,Y, Z. So that's really where we
need to make that connectionsto the human users of that.
And I think that is reallysomething we don't do very
well in project management.
We've done awesome.
We check off, I just leta successful project.
(39:06):
I don't know if we ever go backand really have a conversation
with those who are the recipientof these wonderful things that
we built and explore other kindof improvement opportunities.
Galen Low (39:18):
For me, like I'm very guilty of that.
Like, and I came from an agencybackground, so it literally was
that you roll off a project,it's done, you move on to the
next one, you don't look back.
You don't even have achance to look back.
And I know a lot of folks in mycommunity will say that still.
They'll be like, but David,like, I don't have a chance.
Like they put me on anotherproject as I'm not like part
of this core team necessarily.
I get moved aroundwhere I'm needed.
(39:39):
But I also, it strikes methat like in the healthcare
space, I mean, A, it'sjust so visceral and real.
B, you are impactingthe lives of patients
like real human lives.
And there is an opportunity, Ithink in some cases at least.
To revisit that and likeiterate on a project as part
of an initiative, right?
(39:59):
Like it didn't end there.
Right?
It kept going.
We're still evaluating, right?
The outcomes, I guess.
I mean, the other thing thatstrikes me is that I'm like,
healthcare sounds cool.
It sounds serious.
It sounds like hard work.
The stakes are very high, but.
It's a very relatable lens to belike, how did that go for you?
You know?
Now we have this whatevermedical fall prevention device
attached to you, or now thatwe've got the like sort of
(40:21):
ambient listening now that we'vegot, you know, these tools,
like how is this going for you?
Because it matters interms of the way we take
care of populations.
Then I guess the other sideof me is like, I touched
healthcare a little bit inmy past, but like I'm talking
like hospital websites,you know, not like clinical
systems, not like actualsort of patient solutions.
I'm not a medical professional.
(40:43):
I have had no training there.
But for folks listening whofind this interesting, maybe
they're leading projects, butlike in a different industry,
but they want to like actuallymake the shift into healthcare.
Either A, because you know,they're mission aligned, or
B, it just sounds really cool.
For folks who are likelooking to make a pivot into
leading healthcare projects.
What skills or knowledgeshould they be seeking out?
(41:05):
Do they need to becomedoctors and nurses?
Where should they befocusing their training?
Because I think the otherthing you said there in
there was like, yes, it'sabout getting the right
training to be successful.
David Doan (41:17):
Yeah, that's a great question.
And for everyone who listens,the big response or answer
is no, absolutely no.
You do not need to be aclinician of any sort to add
value in any healthcare project.
In fact, I think what isreally needed is more people
who have fresh perspectivesand different industries to
(41:37):
really cross pollinate and beable to not have healthcare
be mystified and be siloedlike it has been in the past.
So as far as what skills areneeded, just merely being a
project manager, you alreadyset yourself up for success
because when you get yourproject management professional,
or PMP certification or thelike, you are actually being
(42:00):
asked to be able to leadproject in any industry.
So that's a given.
The second is really about,I really think about when I
go back to the PMI (42:07):
Next, and the more that I referred to
earlier is about influencepeople and having effective
communications to affect change.
And that requires leadershipskills and that really
apply to any industry.
I think there's an opportunityfor younger cohorts to really
(42:27):
take advantage of the AI anddata literacy and fluency,
because everything we talkabout AI really needs to start
with the foundational datagovernance, data normalization,
standardization, data integrity,you name it, you can just
do a little Google search.
So having to passion to learnmore about data and AI or
(42:47):
this data literacy in generalis an awesome skillset.
We need more people like that.
And then I think that you mightneed to be mindful of certain
industry and healthcare isone that is everyone knows is
highly regulated, just like thefinancial or banking industry
being exposed to learning about.
When I mentioned CMS earlier,or the CDC, everyone have
(43:08):
heard about HIPAA or theFederal drug administration.
I think get more immersed inwhat are some of the regulatory
requirements that has come downthat we all need to be aware of.
Even people who areclinicians are learning
those regs as we speak.
So don't feel like justbecause you're not a clinician,
we are just interpretingit as quickly as the next
(43:29):
person, regardless of ourclinical background or not.
In fact, like CMS-0057,which is the interoperability
and prior authorization,reg, the final rule was
published in a lot of it'stechnology, like I am trying
to understand the technologylens of it, and I think.
Lastly is having somesense of empathy, and that
shouldn't be hard at all.
(43:51):
I think people get intohealthcare is because you
might have a personal storyor you have a loved ones,
whether that's your brother,your sister, your grandparents
that have gone through what Icall the care journey and you
didn't feel like it was ideal.
That is what drives you,and that's the intrinsic
motivation that feed thepurpose, and that is the
passion that comes through.
(44:12):
When you work with any project.
Imagine that gets translatedinto project that you are
leading in healthcare.
It'll become evident thatyou listen for nuances
and you care about who'sactually delivering the care.
So what I think is empathysometimes helps as well,
and it has nothing to dowith being a clinician.
It helps you to be curiouswith a sense of humility
(44:34):
and the ability to translateand make connections from a
technologist, data science toan infrastructure person, to
a QA person, and ultimatelythe various clinicians.
So, no, you do not, and wewelcome speaking on behalf of
my other colleagues to have.
People who are engineer, youknow, engineers and financial
people to really do a lot ofwhat I call the QA to help
(44:58):
us to make sure that we areleveraging the diversity of
thoughts, but also skills.
Galen Low (45:03):
I love that.
I also love that it's likein finding that empathy,
almost everyone has astory of going through some
sort of healthcare journeythemselves or their loved
ones, or someone they know.
And then isn't it so humanto be like, and this part
of it could have been betterand anchoring around that
to drive your curiosityto be like, you know what?
(45:24):
And you know, I know somepeople in my life, you know,
who are very inspiring,who were impacted in some
way by some kind of healthevent or health crisis.
And have taken up themantle to learn, right?
To be like, okay, wellI need to learn as much
about this as I can.
Even if that means me readingmedical journals that I only
kind of understand and justlike using the tools available
(45:44):
to me to get smart about this.
And the same could be truepivoting into healthcare.
It's not like these answersare inscribed on some scroll
that's hidden in a templefar away you can get at it.
The HIPAA stuff, it's like,sure, it's gonna be dense,
it's gonna be a challenge,but it's out there.
And if you're committed to it,then you know you're learning.
And guess what?
Everyone else is learning too.
You're not necessarilythat far behind.
(46:05):
It's those perspectives andthat empathy that really
kind of drives it through.
David Doan (46:09):
Well, summarized Galen.
Galen Low (46:10):
Well, well said for in the first place.
This has been a lot of fun.
I know we could go on for days.
I'd love to have youback to talk about
measurable health outcomes.
But maybe to wrap it up,just for fun, do you have a
question you wanna ask me?
David Doan (46:26):
Oh my gosh.
I was waiting for thisopportunity 'cause I
wanna learn from you too.
I would say that for someonewho knows project management
well and interact and learn fromother project leaders week after
week in different industries.
I would say what would be kindof the big trend out there or
the shift in mindset of thinkingwhen you're seeing like digital
(46:49):
projects outside of healthcare,what can be taken from someone
who is so deeply immersed inhealthcare that it's almost
like project management lessonfor healthcare practitioner to
learn from other industries.
Galen Low (47:05):
I mean, I think it probably happens more in
healthcare than I assume,but I would say like this
sort of cross training,cross pollination between
strange roles that don'tnecessarily talk to one another.
So let me kind ofzoom out from there.
What we're finding sometimes ina good way and sometimes in a
bad way, but digital teams areexpected to do more with less.
Maybe that's true acrossthe board, but in other
words, we see a lot oflike role hybridization.
(47:28):
You know, you're responsiblefor this and this.
You're a business analyst andyou're a project manager, or
you're an account manager andyou're in business development.
And so there's is sortof like collapsing.
And then the other thingwe're seeing is that we're
at like different roles arecoming into the mix because.
This is, I'm dating backof ways, but on a project
I was working on a whileback, we were working with
someone who was a linguist.
'cause we were doing naturallanguage processing on customer
(47:49):
data and customer feedback.
And it was just like thesecollisions of people who
know different things.
And they don't look likethey should fit together.
But if everyone can kindof start seeing from their
perspective and learningfrom one another, then
it can like diversify theway we think of a team.
And like, I think that inany industry we get fixated
on like, what people dowe need to do X or Y.
(48:11):
And we're like, oh yeah, A, B,C. It's like always this team.
We can actually switch itup a lot more to get some of
these different perspectives.
We can intentionallylearn from one another.
And then I think along theway, for better or for worse,
I think we'll be able todo more than just one job.
And that might be an assetactually in like the age of
AI remains to be seen though,because right now it looks
like cost cutting and leanbudgets and employers trying
(48:34):
to get more from their talents.
I think there's an optimisticupside as well from all of this,
which is I think it does sortof level us up and get us used
to working with different peopleand getting us thinking about
things a little bit differently.
David Doan (48:45):
That was very useful, Galen, really.
You know, I'm on top ofit, so I need to make sure
I remember what you sharebecause healthcare can benefit
from implementing just that.
Absolutely.
I know we talk a lot.
I hope that some of thisanswers start with your
curiosity and others as well.
Galen Low (49:04):
Oh, absolutely.
David Doan (49:04):
But it is been a delightful just to just
share, you know, bouncing backquestions and answer responses.
So I learned quite a bit.
Galen Low (49:12):
Ditto here.
This has been a reallygreat conversation.
Thank you again for your time.
Just for folks who arelistening, where can
people learn more aboutyou and what you do?
David Doan (49:21):
I'm relatively active on LinkedIn, so
I really invite peopleto connect with me.
And, you know, for thelast month or so I've been
inspired to write my LinkedInblog, so by the time this
even gets published, Iwill likely have a blog.
And my blog is really arounda handful of topics that I'm
very passionate about to showkind of my multidimensional,
kind of authentic self.
(49:41):
It's not just about healthcareand technology, which I'm
deeply passionate about.
It has taken me so many yearsof making sure that technology
should enable, you know,what the business user need.
Like the strategy should notbe driven by technology only.
It should be drivenby the business and
the clinical leaders.
The other thing I'm passionateabout is I mentioned
health equity a lot.
(50:02):
It's not just because it's oneof the five quintuple aims is
obviously I'm an Asian person.
You know, I'm not just anAsian leader or anything like
that, is I have my own personalexperience with health and
I truly see it with my momand my grandparents as far as
how their care journeys is.
So I think the discussionand the opportunities now,
(50:22):
health equity is importantfor me to highlight.
You know that I'm a passionateadvocate for project
management in general.
That's why I definitely havevolunteered for many years.
But how do we bring the projectmanagement lens to everything?
But it is more strategic projectmanagement and my nonprofit,
(50:43):
it is a lot of synergies whereI think there's about giving
back and putting it forward.
It is not just bringinga team along, but how do
you see the community?
And the community can be definedas your local city or county,
but sometime our communityis global in some ways.
So I think all theseare topics that I invite
people to come read moreabout on my LinkedIn blog.
Galen Low (51:05):
That's super cool.
I like that the blog is whereit kind of all comes together.
I'm super interested to tune in.
I will include links toyour LinkedIn and your
blog when this goes live.
I'm super excited.
David, thank you again.
David Doan (51:17):
My pleasure.
Thanks so much, Galenfor the conversation.
Galen Low (51:21):
That's it for today's episode of The Digital
Project Manager podcast.
If you enjoyed thisconversation, make sure
to subscribe whereveryou're listening.
And if you want even moretactical insights, case studies
and playbooks, head on over tothedigitalprojectmanager.com.
Until next time,thanks for listening.
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