The Digital Project Manager

How Project Leaders Can Close The Trust Gap In AI-Powered Projects

• Galen Low

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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:

Galen Low:

What role do project leaders play in building this trust within AI healthcare projects?

David Doan:

Project managers are not just task master. They should be framing an AI project as not just a technology deliverable, but it's a human-centered change. It's integrating that technology with what I call humanizing the AI project.

Galen Low:

Why is it so important that healthcare finds ways to adopt AI?

David Doan:

What is that stake ultimately is more than efficiency and effectiveness. This has a direct impact to patient care. If that adoption fail, there's a grave risk of patients may miss out on potential life saving interventions. There may be misdiagnosis if the predictive of modeling does not make sense, especially if AI models are trained on incomplete data. Therefore, the marginalized population may face worse health outcomes.

Galen Low:

Healthcare is so interesting because it's that rigor by default. It has that many stakeholders with that many different perspectives, and so it's almost one of the most complex versions of the game of implementing AI to create solutions that drive better outcomes for humans. Welcome to The Digital Project Manager podcast — the show that helps delivery leaders work smarter, deliver faster, and lead better in the age of AI. I'm Galen, and every week we dive into real world strategies, new tools, proven frameworks, and the occasional war story from the project front lines. Whether you're steering massive transformation projects, wrangling AI workflows, or just trying to keep the chaos under control, you're in the right place. Let's get into it. Okay, today we are talking about the immense potential of AI in healthcare and what project leaders can do to build trust, raise risks, champion ethics, and ultimately drive patient outcomes through AI powered healthcare projects. My guest today is David Doan, Director, Consult Partner for Healthcare& Government at Kyndryl. David is a healthcare technology and business transformation leader with over 30 years of clinical and consulting experience. He started his career at the bedside as a registered nurse for the first 10 years and then went on to consult at McKesson, Accenture, Ernst& Young, and is now partnering with C-Level and IT executive clients to drive strategic digital transformation, AI innovation, and value-based care initiatives at  Kyndryl. Beyond that, David is the president of PMI Los Angeles chapter, serves on the board of directors of five other nonprofit organizations, is a mentor for the Asian American Professional Association, and so far that's only half of his rap sheet of accolade and accomplishments. It's very impressive, David. Thank you for being on the show.

David Doan:

My pleasure, Galen. Absolutely.

Galen Low:

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 hoping that we can just cover just the excitement and the fear surrounding AI enhanced patient care and what can be done to address both. Maybe just like what's at stake for our healthcare industry if we don't get AI, right? How a framework of trust can help project leaders align disparate stakeholder groups. And maybe just how project leaders would know previous healthcare experience can get into the healthcare space and maybe vice versa. How does that sound to you?

David Doan:

That's wonderful. Great discussions, great questions. I have my work cut out, but I'm pretty sure I can provide a little bit of insight based on my experience. But yeah. Great discussion.

Galen Low:

Well, if I learned anything about you so far, it's that you're fast on your feet and you know your stuff. So I'm gonna challenge you. I'm gonna challenge you. We've got this tradition here where I kind of start with like the big question, the one hot question that we can then sort of zoom out from and then build the context around. So my big question is this, what is the biggest fear that clinicians and medical practitioners have when it comes to AI being introduced into the way that they deliver care?

David Doan:

Yeah, great questions. Very relevant one. I summarized it in kind of two topics. One is the fear of losing human connection and judgment is one. So I touched on that. And the second is really the fear of accountability. So I actually started my nursing career writing. Literally writing, you know, there's no such thing as an electronic health record or electronic medical record. And when we move into technology, even just giving medications out of this machine called Pyxis Machine, we always were fearful of how is that going to disconnect us with the patient somehow. AI is definitely another example of advanced technology that can actually do that. So for example, now there's a AI tool, machines and predictive, you know, machines that can actually read the film from a chest x-ray or a PET scan. So there's that fear of not being able to actually, you know, touch and feel and having that human connection and also the judgment as you know, you know, medicine, nursing. 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 piece of the puzzle in healthcare is really the clinical judgment. That's really what differentiate between a nonclinical staff versus a clinician that has, you know, a license that they need to practice at the top of the license, but also a sense of accountability as well. So I think that the fear where AI can actually replace conversations and dialogues with patients at the bedside, or even when you adopt visiting a doctor visits or even sometime when you have telehealth or telemedicine, is that they fear that they cannot and should not lose. Really the clinical judgment and their decision making. So whatever technology or tool, that is one thing that we need to really address and it needs to be collaborative with the clinicians. So algorithm that spit out predictions. They need to make sure that the data is insightful at the point of care, but really appreciate the need for the clinician to understand and trust the data and the insight, but really preserve that sacred clinicians and patient relationships, so that way they're still somehow providing data, clinical judgments that help inform the decision making. The accountability piece is important too because you know in medicine, clinicians are trained to do no harm. We wanted to make sure that the AI or technology model actually works, and that way it makes recommendations that it is consistent, aligned with evidence-based guidelines and all of the other reputable professional organizations recommendations. That accountability really rests on, can clinicians still have that final review to make sure that they still ultimately accountable for it, but the AI system, or the technology and the engineer around that, there has to be some due diligence to ensure that 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 it down, is really about the human connections or making sure that there's no loss of that, and that also the clinical judgment. And second is the role of accountability of a clinician, but also from the technology side.

Galen Low:

I love that and like I like that you framed it around the fact that it's like an art and a science. Right. And I think sometimes it's easy to get swept up from a very high level of, oh, it's just information. We can upload all of our medical knowledge and then that information will be available. But I also like the other thing you did there, which I don't know if you meant to do it, but there have been a lot of disruptive technological progressions in the healthcare industry. You mentioned some of the prescription apps. We're talking about telehealth. There's been a lot of things, and I think. What I like about your answer there is that these are the underpinnings that have helped us get through all of this change. And I know like EHR, like the electronic health records or electronic medical records, it's been a long journey, hasn't it? Right. At my time in consulting, we're still transitioning systems over. In some ways. It's not just technological progress. It's like we're still building trust and we're still being careful because of that oath, because we can't just assume that something that happens in a black box is gonna work well every time or 90% of the time. Like that isn't quite good enough. It's the judgment and it's the sort of humanity that needs to stay in it. I think it's fascinating. And then also I just think that idea of the consistency, you mentioned consistency, and immediately my head went, oh yeah, hallucinations in AI. It's fine in my work, right? It's like, wait, hold on. That was not the answer that I was looking for. Or even I asked it the same question three times and got three different answers. That's fine, I can fix that. But like when it comes to patient care, that is something that we have to do very Right. And I'd be very careful about, so I know that's all the Right, yeah. Important things. But I wondered if maybe we could zoom out a little bit because. We've been talking a little bit about accountability and trust, the patient experience and the humanity of it. We talked a little bit along the way about sort of some technologies and technology always does find its way into healthcare for good reasons. AI seems a little bit different in some ways, or maybe it's not, but I thought maybe I'd just kind of ask why is it so important that healthcare finds ways to adopt AI? What's at stake here and what's like the biggest barrier that AI adoption faces in healthcare?

David Doan:

What is at stake ultimately is more than efficiency and effectiveness of how clinicians interact with their member or patient or the healthcare delivery team.'cause there's a whole team that managed the patient is ultimately, really result to positive or health outcomes. So there is such big ramification and consequences and consideration to think about. It's not just making someone's workflow easier, having a better experience. Ultimately this has a direct impact 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 in what I call on a massive scale called population health. And it also aligns with. The quintuple aim, where it's not just about costs, it's not just about access, it's now about the clinician experience, the patient experience. And finally, at the tip, which is the fifth kind of layer of this kind of triangle is health equity. So where does AI come into that? AI can definitely, certainly predict the diseases taking in so much data, the clinical data, the claims data, the nonclinical data, the publicly available data and so on. All of that helps to predict which patient cohort or populations that the providers or the health plan or payer can identify quickly to intervene to kind of slow the progression of any disease state chronic conditions. Now if that adoption fail, what you can see is there are patients that should be managed and they're not, or they have been identified of having something that they are not they're not appropriate. There's also an opportunity where there's a grave risk of patients and members may miss out on potential lifesaving interventions. There may be misdiagnosis if the machine or the modeling tool does not make sense. And when we think about technology, there's also a lot of people who don't live in large metropolitan cities, in rural populations where there's critically accessed hospitals. We are still being challenged with technology. The technology may be available, but the 5G connection and network connection, the internet connection, or how do we actually manage that? And when I talk about health equity. Are you expecting someone who English may be their, not their first language, but they also are challenged because of dexterity, level of education or age and so on to be able to use whatever telehealth medicine it is? So when you talk about AI, there's a huge implication in what's at stake is ultimately the health outcomes of the population. The biggest barrier, I kind of alluded to it, is a lot of it is there's technology barrier from the receiving of the receiver of care that's your patient's member. But if I were to focus on the clinicians and the care deliverer and also the caregivers, is that really that trust we talk about? But from a technology side, information needs to be interfaced or integrated and immersed into the workflow. So if it's not immersed in the workflow, AI may force the clinician to use another technology, or you have to have a little thing that to record the conversation. Where does that information go? Does it actually immerse or present it in what I call the natural workflow of the clinician? Because if it does not present itself in that workflow, that is really seamless. It's not gonna increase the adoption of the usage of the whatever the technology is, because anything that disrupts the clinician time with patients that will result in poor adoption. And lastly, you know, there are biases. So if AI models are trained on like incomplete, you know, lack of data or the data is not normalized, standardized, or skew in some way, therefore those are the opportunity where patients could. Especially the marginalized population may even face worse health outcomes. So that's what's at stake is massive about health outcomes and then also the adoption of clinicians with technology.

Galen Low:

I'm really glad you went there, especially with the patient and clinician experience. My background's in user-centered design, so like mostly we're like digital solutions that. Yes. You know, solve a problem, make something more efficient, leverage more data, but also fundamentally, yeah, have to be workable. Have to enter into a workflow seamlessly so that it doesn't create an additional barrier. And you were saying up top when you were a registered nurse, you're doing bedside care. You know, you're writing these things by hand. And there is an opportunity to really give some of that time back right to a medical practitioner so that they can focus on patient care. At the same time, not adding like an additional step in there that might actually lead to worse 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 I was chatting with someone last week, we were talking about how AI is sort of, it kinda like levels the playing field in some areas, right? Where right now there's people who are vibe coding, they've never been developers before. They didn't train to be a developer, but now they're able to create an application and vice versa, right? Technical folks who weren't taught or don't consider themselves well versed in like business language now can sort of use some of these tools available to them to sort of have those conversations and like break down some of the silos. And I did a little bit of work in like outpatient care, telehealth sort of stuff from a digital side. And it really opened my eyes. I think you, what you said about folks living in metropolitan areas versus bulk of the population, which doesn't, you know, we're scattered about. The infrastructure is different. The United States in particular has been pretty aggressive about getting broadband everywhere and the 5G transformation. But it's still not everywhere. We can't just assume that everyone has access to all these things. Has the ability to engage with all these things is open to all of these things, and I think that's the big zoom out. Why I think it's super interesting in the healthcare side of things, because unlike some of the things that we talk about in the business world where we're like. Hey, we can get copilot, you know, to be helping us write documents. We're all sort of a certain type of knowledge worker doing a certain type of job. Healthcare is not that. Healthcare is everybody, you know? It impacts everybody. It goes across demographics, it goes across, yeah, a lot of different things, and that's why I think it's such an interesting and juicy topic because even if you're not in healthcare, if you're listening to this and you're not in healthcare. This at least shows that picture of AI at scale, right?

David Doan:

Absolutely.

Galen Low:

With different members of the population for something that really matters, which is the health of our population, patient outcomes, and ultimately health. I did like also what you said about preventative. It kind of got me thinking, you know, predictive analytics, right? It's one of those things that, 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 thinking about things like. You have your health spending account to get like an ergonomic office chair. In some ways, that's preventative care because it's like, okay, if you're not sitting in a garbage chair all the time, then you're not likely to develop back pain, chronic back pain that then we need to treat in a certain way. And then I started thinking about strain on system and I'm like, okay, well there are health administrators, healthcare leaders, and even just the business side of the system going, wow, that's great. Yes, we wanna prevent. Some of these things from getting too far. You said, you know, intervention at the right time to get people the care that they need. And I'm also like, well, some of the folks, don't get me wrong, noble in intention as well, but it's their job to also think about strain on system and like money, right? To be like, well, it gets a lot more expensive to treat people later in their health journey, whereas if we catch it early, that could be cheaper. Then it got me thinking, because you actually are someone who did a decade at bedside as a registered nurse before entering the consulting world, and now you work with chief medical officers, you work with regulators, you work with other decision makers in the healthcare space, but in other words, like you actually are someone who can see things from all the perspectives. It got me thinking about like trust, but also how can trust around AI be built between patients and caregivers and clinicians and regulators and business leaders. They all look at it from a bit of a different perspective and like what's involved in reconciling all those perspectives.

David Doan:

Yeah. You are making me work very hard. But Galen I'm delighted to share my perspective on the hard question. You know, just by you listing all of those names of what I call stakeholders. So in healthcare, it's never a person. It's always what I call a healthcare ecosystem. And that ecosystem may be people that are likely invisible to the patients or the members. Like for example, you mentioned about regulators. So there's accrediting bodies. There's also centers for Medicare and Medicaid services, or CMS and the Center for Disease Control, et cetera. They want governance and they wanna make sure that ultimately the care that is being delivered, whether you use advanced technology or no technology, is actually, you know, quality and is safe. And you also have the patients who want reassurance. Reassurance that you provide practitioners or doctors. Even know about the culture that I am raised up or the language that I speak, because that has a lot to do with the type of food and nutritions that I have a preference on. Obviously clinicians want to see evidence. They are trained to really review what we call peer review articles. It's not just word of mouth that, oh, the CIO or the chief digital officer or data officer said that we need to adapt ambiance. You know, listening AI, that's great, but what's the evidence as far as has there been done any research that shows actually there is a high probability that is correct versus how do we address. Some of the hallucinations, you know, we'll be talking about AI or just really misdiagnosis. So that's reassurance. Like, I don't want to be the first hospital to do this, or the first health plan to do this. Has there been any evidence? When we say evidence, it's not just a blog, it's peer review articles, and that takes time to really build that literature up. And then you said business leader, I hate to say it, it's really about financial performance. Even in a hospital setting, it is a business. So they want to see hard, quantifiable, ROI with these very expensive advanced technology. So let me just give you some suggestions of how to bridge that gap to ensure transparency and having that shared language to really build trust. Because we talk about, yeah, those are the problems. Those are the background that we have to work off of. One is what I call explainability. How do you actually have the data to really think about in plain language? Make the connection from a technologist, from an engineer, from a data scientist, from a product manager talk to a clinician to say they understand the business problems and also the opportunities, meaning the specific use cases that AI can be applied. Can you explain how 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 buy-in, but also allow that, what I call the collaboration, to have the clinician or the business leaders to ask questions because they are so busy, they don't know the details behind the technology. You have to talk about safeguard with information, with data. We have to talk about the connectivity of multiple data, how it gets presented into the workflow at what I call the point of care. Being able to explain that in lay language or playing language on both sides, because the clinicians may be presenting a very specific use case that the technologist may not understand fully what that is. The second is really inclusion in design is you mentioned that you have background user interface, user experience. Well, you have to have the voice 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 need to really consider just because you're a clinician, a pharmacist workflow, as you may already know, is very different than a nurse, than a physicians, et cetera. So those are the things to be considered. The modules within an EHR is configured differently for different floor and different unit, be as inclusive in the design and the implementation and the change management. And then it needs to really be couched around governance. People are rushed into implementing AI without solid policies, without the framework, without the governance structure. I know everyone talk about framework. Everyone has a framework in everything, consulting firm, but we need to carry that out. What are some of the safeguard or the guardrails around. Equity, fairness, bias, privacy, accountability that we need to address. I know that's kind of boring stuff, but without that, you will not be successful in rolling out and the adoptions will not be there. And also this risk on kind of the regulatory side. And lastly is the cultural storytelling. What is this all about? It seems like it doesn't fit, does it? So how does AI improve not just the numbers, the quantifiable ROI, but actually patient lives? Let me give you an example. Those clients that I am able to have the privilege of working who I think got it right, is that they actually tell the technology team that whatever you're building or the requirements that you are writing and that you are testing, if you don't understand how this is used by clinician X or business user X and how that ultimately mapped to the positive experience and health outcome of the patients, then they should have no business working on this project. Brilliant. The technology team should be an extension of the clinicians or the caregiver, so they should be actually caregivers of the caregivers. So that is when I think trust is built. So without that trust through technology, you don't have really the people, the process in place and buy-in. So I think storytelling is about the voice of the customer through conversation, through collaboration that you buy-in and that will help with transparency and therefore trust will be enabled.

Galen Low:

I love how that kind of. You paint it out as an ecosystem, and I think a lot of people understand it as an ecosystem with a lot of stakeholders in it that you know for a cause that really matters, right? People's healths and livelihood. But I love that notion of like even like the product team, the tech team being the caregivers of the caregivers, and it's all actually this. It's one picture that different stakeholders have to look at it from different lenses through different lenses from different angles, like your chief medical officer or you know, those are sort of business lens on things like, yeah, they have to care about money.'cause guess how patient care is delivered, right? It requires funding, it requires money and also. It is something that is like very regulated, right? We have these things in place and it's funny, I like sort of drawing the comparison to, for example, the business world and you and I, we both come from the consulting world, so I think we can say this, but it's every other week that BCG, McKinsey, Accenture, EY, the publishing a report, everyone's sharing it on social media or via email. We're going, oh, that's a good idea. Let's start doing that right away versus like. Has it been in a pure reviewed journal? Right. You mentioned things like ambient AI listening, right. And then I'm like, I haven't been very close to a sort of medical journal recently, but like what an interesting way to sort of vet out these ideas at like the highest rigor of very smart people who understand the technology and the health implications and the human implications. Being critical of one another to sort of make sure that this is the right thing, not just a thing we can try. It's a completely different picture than how a lot of people think about AI. Even folks listening. And maybe a bit of part of me is like, well, shouldn't it be easy? Just try and roll out a little pilot program and then scale from there. Like, you know, be iterative. Isn't that what we always do? No, unfortunately, the CDC also has to be on board, so you kind of have to have.

David Doan:

That's right.

Galen Low:

It's a whole different thing. But I do also think that everyone can take a page outta this book, right? It's almost this like macro view of where we're heading. We started out with AI in the sort of business world, in less regulated areas, just like trying stuff. Then we're gonna run into that governance wall, right? We're gonna run into the data quality wall, we're gonna run into all these things that sound boring to us now. But are gonna matter for everyone pretty soon. And that's why I think healthcare is so interesting because it's that by default, it's that rigor by default, and it has that many stakeholders with that many different perspectives by default. And so it's almost like one of the most complex versions of the game of implementing AI to create solutions. That drive better outcomes for humans. It's really interesting. I love that sort of framework. I wonder if I can bring it back to the sort of the project level as well. I recognize you and I were passionate about this sort of stuff. Like we can talk at a very high level. You know, we've been talking about trust and I kind of frame this around. AI powered or AI related healthcare projects, whether that's implementing AI technology or using it in the project, but it is, it still comes back down to trust. It's, you know, it's quite a complex picture. What role do project leaders play in building that trust? Like is there a responsibility for folks who are delivering some of these projects and just like you said about. The technologists being the caregivers for the caregivers, you know, what role does a project manager play in building this trust within AI healthcare projects?

David Doan:

Well, this is a question that I'm passionate about just because of our kind of connection with project management in general. As you introduced me, I'm the president of our Project Management Institute of PMI, Los Angeles chapter, so I definitely wanted to highlight some of the PMI concept and methodology here in the framework as well. But as far as the role of project managers in building trust, project managers strategically has been able to orchestrate all of the stakeholders and all the project team members. So they are at a very privileged, critical role of being able to see from all and all aspects, I would say project leaders need to first be strategic, but also be able to. Make the translation so that way the clinical, the business and all of the stakeholders kind of understand one another because that is really important that we speak, quote the same language. Why would say, not just speak, but really to understand each other kind of needs and intentions and requirements and all that. And then by being this physician of quarterbacking. You want to be able to then freely and proactively raise risk early and transparently, and think of framing an AI project as not just a technology deliverable, but it's a human centered change. It's integrating that technology with what I call humanizing the AI project where we are reminding project team members that is ultimately for healthcare anyway. I'm speaking from a healthcare industry perspective, is that whatever is being introduced that is ultimately going to hopefully increase productivity, that yield more what I call FaceTime with the patients or members. And that somehow would result in kind of a positive health outcomes. I think it's all about outcomes. That could be a whole topic of discussion, is how to even measure health outcomes and what are the vehicles and the data that will be needed. So back to project management. I have been an advocate of project managers on not just task master, and we are not here to just tell people when to do things and how to do things and all that, because you can have a robot doing that. I think project managers are not being tapped into the visionary, strategic problem, critical thinking skills. Let me give an example. I'm gonna reference president of PMI, Pierre Le Manh, and he and his team introduced a concept called PMI:Next, and that was probably about two years ago. And I think chapters and project leaders are still trying to understand what that is. So to me, how I interpret that is really the vision of what PMI or project management in general. So what is that vision? So we tend to say that the vision is really about. The purpose of what it is that we are doing to elevate the project success that enables some sort of transformative change in the world. It needs to rely on strategy, being able to not just deliver the value of tools, but enable continuous learning. There's also kind of the culture values and then the framework that helps support that vision or executing that vision is what PMI call it MORE. It's an acronym, MORE, which is really maximizing the success through not just traditional metrics. We are very familiar with what I call scope, budget, and schedule. But what is really the outcome or the positive impact in healthcare that will be positive health outcomes? Are we actually saving lives? Are we actually increasing the longevity of how patients live, not just in number of years, but the quality of their experiences in how they live? Are they actually changing behaviors? Those are positive health outcomes. How do we organize the impact by empowering our professionals to really build a stronger community? And how do we reinvent and reengage the ecosystem of stakeholders? So all these things are so important as what the role of a project leaders or managers have in any project, but particularly in healthcare enabling AI is really adopting that kind of mindset of PMI:Next and PMI MORE. So that is the role. A very important role of a strategic project manager has in leading projects technology project in healthcare.

Galen Low:

I love that. I love the tie in with being the translator, the translating quarterback, and how it ties into like your explainability, right? Like there's a very human element there. Even just the fact that you said 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 know, very inspiring graphics on my LinkedIn feed that are like, you know, be more strategic. Let's AI elevate you into a more human role, yada, yada, yada. But actually this is like more than just words. This is like actually okay, this is how it looks. And especially in the healthcare space where it is about patient outcomes and actual, you know, impacts to livelihood. I guess the devil's advocate in me, 'cause I think you touched on it earlier, right? You're like, there's still people wrapping their heads around this. It's been a couple years. These frameworks are relatively new in the grand scheme of project management. But also I think they're difficult because. I think the critics would say, well, Pierre's just trying to turn every project manager into like a strategic C-suite executive. And yet there's this big gap, right, between learning how to manage scope, schedule, and budget, and understanding your industry and the people within it so well that you can influence outcomes. It almost seems like a unfathomable leap. But of course it's possible because I do see people do it every day. I'm like, what do you think that leap looks like for folks? Like if you've been leading projects in the healthcare space, but you've had the luxury 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 their journey towards the MORE framework, the where they can think about outcomes, where they can think about maximizing the impact of their projects?

David Doan:

Yeah, that's a great question. I think as like a maturity model or curve. So for example, if someone who just graduated from the university, whether they have an MBA or not, and they want to do project management. If we wanted to focus on the project manager role, first of all, they need to actually know how to project, manage or manage a project. What is the methodology? Whether you are leaning on PMI or you are leaning on Agile or Scrum, there's so many variation of that. So then it takes a few years, I think, to really understand the mechanics and the methodology of it. Once you master that. I think project managers are going to get to a point where they feel like they can do in the sleep, but that's always as we know, a trigger or a flag or an alert that you need to be challenged and you're not probably learning. So what we wanted to do is. You know, project manager one, two, three, or what we call project coordinator, become project manager to become program manager, portfolio manager. So that is an evolution for those who aspire to really think broadly about the impact of how effective projects are being done. We'll not just say cost and being efficient about it, but also when you get a product or a service out sooner, the end users will take advantage of that and outcomes will be realized. And then we also need to really, I think, take credit for the things that we do so well in project management. Because we need to speak the language of what's the ROI from many different lens, not just the quantitative dollar investment and dollar save and reduction in readmissions, or reduction in or increase in revenue because we get incentivized for doing something great in healthcare. How is that actually going to make a difference in a population or a community or a marginalized population? I think that's a call to action for project manager to, I think, have a pathway to get there. I don't expect anyone to just change that mindset, but I think it needs to be taught. It needs to be trained. It needs to have an opportunity for those who may not already. A strategic thinker, first of all to have the opportunity to do this. And I would say I challenge kind of the PMO or the project manager office organizations and the leaders of the organization to really provide the training, but also the opportunity and all the support to make sure that we think strategically.'cause that's how you evolve as a leader, whether you're a project manager or not. So that's really the challenge, a call to action. And I truly believe that people do want to make connections of what they do. How is it that is impacting anyone? So I do think people inherently want to know. The legacy, that's a strong word to use, but the impact that they leave behind when they successfully do something, but yeah.

Galen Low:

That's probably the clearest answer I've ever gotten to that question, by the way. Well, what I like about it is that yes, it is aspirational. No, nobody expects you to be doing it day one. It's a maturity model. You get there. And also some of the things that we're talking about project managers are doing every day and not getting recognized for it, right? It's like it's not that big of a leap. When you stop thinking about project management as scope, schedule, budget, you know, measurable dollar outcomes or KPIs that are fundamentally not the KPIs, right? They're just like indicators, 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, we are driving towards outcomes. So even though it sounds like a big leap on paper. When you kind of frame it the way you have, you're like, yeah, no. It's just like the journey can continue up. I love that about the, if you feel like you can do it in your sleep, yeah, you probably do need to get challenged. And I think the path does go higher than what we think of, you know, we're like, oh, senior project manager, I guess you've topped out and then just make some lateral moves and that's your career. But actually there's an opportunity to. I think legacy is a strong word, but not too strong of a word when you're talking about projects that are transforming lives. And I think that's yeah, that's a really good way of putting it.

David Doan:

Yeah. I would just challenge the project 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 go back to the end user that it was intended for and ask them, how did the technology work for you? How do you feel as far as trusting the technology? Like asking these questions, you get that qualitative kind of feedback, but you also probably hear 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 connections to the human users of that. And I think that is really something we don't do very well in project management. We've done awesome. We check off, I just let a successful project. I don't know if we ever go back and really have a conversation with those who are the recipient of these wonderful things that we built and explore other kind of improvement opportunities.

Galen Low:

For me, like I'm very guilty of that. Like, and I came from an agency background, 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 a chance to look back. And I know a lot of folks in my community will say that still. They'll be like, but David, like, I don't have a chance. Like they put me on another project as I'm not like part of this core team necessarily. I get moved around where I'm needed. But I also, it strikes me that like in the healthcare space, I mean, A, it's just so visceral and real. B, you are impacting the lives of patients like real human lives. And there is an opportunity, I think in some cases at least. To revisit that and like iterate on a project as part of an initiative, right? Like it didn't end there. Right? It kept going. We're still evaluating, right? The outcomes, I guess. I mean, the other thing that strikes 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 be like, how did that go for you? You know? Now we have this whatever medical fall prevention device attached to you, or now that we've got the like sort of ambient listening now that we've got, you know, these tools, like how is this going for you? Because it matters in terms of the way we take care of populations. Then I guess the other side of me is like, I touched healthcare a little bit in my past, but like I'm talking like hospital websites, you know, not like clinical systems, not like actual sort of patient solutions. I'm not a medical professional. I have had no training there. But for folks listening who find this interesting, maybe they're leading projects, but like in a different industry, but they want to like actually make the shift into healthcare. Either A, because you know, they're mission aligned, or B, it just sounds really cool. For folks who are like looking to make a pivot into leading healthcare projects. What skills or knowledge should they be seeking out? Do they need to become doctors and nurses? Where should they be focusing their training? Because I think the other thing you said there in there was like, yes, it's about getting the right training to be successful.

David Doan:

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 a clinician of any sort to add value in any healthcare project. In fact, I think what is really needed is more people who have fresh perspectives and different industries to really cross pollinate and be able to not have healthcare be mystified and be siloed like it has been in the past. So as far as what skills are needed, just merely being a project manager, you already set yourself up for success because when you get your project management professional, or PMP certification or the like, you are actually being asked to be able to lead project in any industry. So that's a given. The second is really about, I really think about when I

go back to the PMI:

Next, and the more that I referred to earlier is about influence people and having effective communications to affect change. And that requires leadership skills and that really apply to any industry. I think there's an opportunity for younger cohorts to really take advantage of the AI and data literacy and fluency, because everything we talk about AI really needs to start with the foundational data governance, data normalization, standardization, data integrity, you name it, you can just do a little Google search. So having to passion to learn more about data and AI or this data literacy in general is an awesome skillset. We need more people like that. And then I think that you might need to be mindful of certain industry and healthcare is one that is everyone knows is highly regulated, just like the financial or banking industry being exposed to learning about. When I mentioned CMS earlier, or the CDC, everyone have heard about HIPAA or the Federal drug administration. I think get more immersed in what are some of the regulatory requirements that has come down that we all need to be aware of. Even people who are clinicians are learning those regs as we speak. So don't feel like just because you're not a clinician, we are just interpreting it as quickly as the next person, regardless of our clinical 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's technology, like I am trying to understand the technology lens of it, and I think. Lastly is having some sense of empathy, and that shouldn't be hard at all. I think people get into healthcare is because you might have a personal story or you have a loved ones, whether that's your brother, your sister, your grandparents that have gone through what I call 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 the purpose, and that is the passion that comes through. When you work with any project. Imagine that gets translated into project that you are leading in healthcare. It'll become evident that you listen for nuances and you care about who's actually delivering the care. So what I think is empathy sometimes helps as well, and it has nothing to do with being a clinician. It helps you to be curious with a sense of humility and the ability to translate and make connections from a technologist, data science to an infrastructure person, to a QA person, and ultimately the various clinicians. So, no, you do not, and we welcome speaking on behalf of my other colleagues to have. People who are engineer, you know, engineers and financial people to really do a lot of what I call the QA to help us to make sure that we are leveraging the diversity of thoughts, but also skills.

Galen Low:

I love that. I also love that it's like in finding that empathy, almost everyone has a story of going through some sort of healthcare journey themselves or their loved ones, or someone they know. And then isn't it so human to be like, and this part of it could have been better and anchoring around that to drive your curiosity to be like, you know what? And you know, I know some people in my life, you know, who are very inspiring, who were impacted in some way by some kind of health event or health crisis. And have taken up the mantle to learn, right? To be like, okay, well I need to learn as much about this as I can. Even if that means me reading medical journals that I only kind of understand and just like using the tools available to me to get smart about this. And the same could be true pivoting into healthcare. It's not like these answers are inscribed on some scroll that's hidden in a temple far 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 necessarily that far behind. It's those perspectives and that empathy that really kind of drives it through.

David Doan:

Well, summarized Galen.

Galen Low:

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 you back 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:

Oh my gosh. I was waiting for this opportunity 'cause I wanna learn from you too. I would say that for someone who knows project management well and interact and learn from other project leaders week after week in different industries. I would say what would be kind of the big trend out there or the shift in mindset of thinking when you're seeing like digital projects outside of healthcare, what can be taken from someone who is so deeply immersed in healthcare that it's almost like project management lesson for healthcare practitioner to learn from other industries.

Galen Low:

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't necessarily talk to one another. So let me kind of zoom out from there. What we're finding sometimes in a good way and sometimes in a bad way, but digital teams are expected to do more with less. Maybe that's true across the board, but in other words, we see a lot of like role hybridization. You know, you're responsible for this and this. You're a business analyst and you're a project manager, or you're an account manager and you're in business development. And so there's is sort of like collapsing. And then the other thing we're seeing is that we're at like different roles are coming into the mix because. This is, I'm dating back of ways, but on a project I was working on a while back, we were working with someone who was a linguist.'cause we were doing natural language processing on customer data and customer feedback. And it was just like these collisions of people who know different things. And they don't look like they should fit together. But if everyone can kind of start seeing from their perspective and learning from one another, then it can like diversify the way we think of a team. And like, I think that in any industry we get fixated on like, what people do we need to do X or Y. And we're like, oh yeah, A, B, C. It's like always this team. We can actually switch it up a lot more to get some of these different perspectives. We can intentionally learn from one another. And then I think along the way, for better or for worse, I think we'll be able to do more than just one job. And that might be an asset actually in like the age of AI remains to be seen though, because right now it looks like cost cutting and lean budgets and employers trying to get more from their talents. I think there's an optimistic upside as well from all of this, which is I think it does sort of level us up and get us used to working with different people and getting us thinking about things a little bit differently.

David Doan:

That was very useful, Galen, really. You know, I'm on top of it, so I need to make sure I remember what you share because healthcare can benefit from implementing just that. Absolutely. I know we talk a lot. I hope that some of this answers start with your curiosity and others as well.

Galen Low:

Oh, absolutely.

David Doan:

But it is been a delightful just to just share, you know, bouncing back questions and answer responses. So I learned quite a bit.

Galen Low:

Ditto here. This has been a really great conversation. Thank you again for your time. Just for folks who are listening, where can people learn more about you and what you do?

David Doan:

I'm relatively active on LinkedIn, so I really invite people to connect with me. And, you know, for the last month or so I've been inspired to write my LinkedIn blog, so by the time this even gets published, I will likely have a blog. And my blog is really around a handful of topics that I'm very passionate about to show kind of my multidimensional, kind of authentic self. It's not just about healthcare and technology, which I'm deeply passionate about. It has taken me so many years of making sure that technology should enable, you know, what the business user need. Like the strategy should not be driven by technology only. It should be driven by the business and the clinical leaders. The other thing I'm passionate about is I mentioned health equity a lot. It's not just because it's one of the five quintuple aims is obviously I'm an Asian person. You know, I'm not just an Asian leader or anything like that, is I have my own personal experience with health and I truly see it with my mom and my grandparents as far as how their care journeys is. So I think the discussion and the opportunities now, health equity is important for me to highlight. You know that I'm a passionate advocate for project management in general. That's why I definitely have volunteered for many years. But how do we bring the project management lens to everything? But it is more strategic project management and my nonprofit, it is a lot of synergies where I think there's about giving back and putting it forward. It is not just bringing a team along, but how do you see the community? And the community can be defined as your local city or county, but sometime our community is global in some ways. So I think all these are topics that I invite people to come read more about on my LinkedIn blog.

Galen Low:

That's super cool. I like that the blog is where it kind of all comes together. I'm super interested to tune in. I will include links to your LinkedIn and your blog when this goes live. I'm super excited. David, thank you again.

David Doan:

My pleasure. Thanks so much, Galen for the conversation.

Galen Low:

That's it for today's episode of The Digital Project Manager podcast. If you enjoyed this conversation, make sure to subscribe wherever you're listening. And if you want even more tactical insights, case studies and playbooks, head on over to thedigitalprojectmanager.com. Until next time, thanks for listening.