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Physician executive Aiden Feng discusses the article, “Rising ER wait times signal larger health system challenges.” In this episode, Aiden examines how increasing ED wait times reflect deeper systemic issues in the U.S. health care system, including staffing shortages, fragmented digital health solutions, and declining operational efficiencies since the pandemic. He explores the impact of isolated point solutions versus integrated technology approaches and emphasizes actionable strategies such as leveraging AI for triage and automating administrative processes. Aiden highlights the need for comprehensive, system-wide reforms to improve patient flow and reduce delays in emergency care.
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Transcript
Kevin Pho: Hi, and welcome to the show. Subscribe at KevinMD.com/podcast. Today we welcome Aiden Feng. He’s a physician executive. Today’s KevinMD article is “Rising ER wait times signal larger health system challenges.” Aiden, welcome to the show.
Aiden Feng: Thank you so much, Kevin. Thanks for having me. Great to meet you.
Kevin Pho: All right. So tell us what led you to write and submit this article on KevinMD?
Aiden Feng: Yeah, you know, I think it’s about exposing some of the paradoxes we’re seeing in health care, and specifically, what motivated me was an issue that extends far beyond the emergency department but is manifested in the ER specifically. That is, you know, in all other industries, with the implementation of technology, there’s usually exponential growth in productivity and capacity creation and experience improvements for both workers and, and customers—in our case, patients.
But what’s surprising for us is that billions of dollars have been invested into EHRs and all these digital health solutions, and the result is interesting. It’s that, you know, I think, in an article I mentioned in terms of productivity and wait times in the emergency departments, and despite technology investment, we’ve actually become less productive in health care. That was the core question in my mind as we did a deeper dive into this arena and specifically in the emergency department.
Kevin Pho: All right, so tell us a little bit more about how that influx of technology actually makes us less productive, certainly in the emergency department setting. So give us more detail.
Aiden Feng: Yeah, you know, I think there are many compounding variables, right? This is not just—if I remember my statistics class—it’s a multivariable regression, not just direct cause and effect. You know, with COVID, ER volume and hospital volume dropped, and then obviously staffing went down. As we’ve returned back to normal, volumes have increased, and then, you know, there’s been a lot of staffing shortages. That’s one component.
But in terms of the technology component, I think what we have seen in the market has been a disconnect between how technology is deployed, right? There is the source of truth, the foundational layer of the EMR that’s optimized for record keeping, optimized for billing, and then that’s a single source of truth. But the layer on top of that—to automate workflows, to curate patient experiences and journeys—is a very fragmented ecosystem, full of dead ends. A lot of the health systems that we go around and speak to and partner together with, they have deployed five to seven to ten of those. They work very hard—each of them has to integrate into the EHR to pull and push data—but they also try to cobble them together to create one experience. That is very, very hard because there are conflicting incentives.
What the result is, there are a lot of dead ends for patients, for providers, and then there’s a lot of soul-crushing toggling between different systems. I think that is one of the core causes of this manifestation we just talked about earlier.
Kevin Pho: So give us a case study so we can see it both from the clinician’s standpoint and the patient’s standpoint. Tell us some of these cobbled-together technology solutions that lead to these dead ends. Let’s say from a physician’s standpoint, what would exactly that look like?
Aiden Feng: Yeah, for sure. I’ll just give you one quick example, right? If you go to some of these health system websites and you say, “I have pink eye,” there are three scenarios that could happen. One: “I do not understand what you wrote. Can you please say that again?” or “Call this number,” and then, you know, again, introducing burden. Two: “Here’s a link to our ophthalmologist,” and you know, that is an ophthalmologist’s worst nightmare, right? To get a healthy pink-eye patient in their clinic slot. Three: it actually understands your intent and then guides you to a virtual urgent care visit that can happen immediately, right?
That’s just one quick example. The first two scenarios introduce more complexity into the system rather than the last, and then all of a sudden, you’re either at a dead end or you’re on a wild goose chase that takes, you know, someone on the phone or a triage nurse in the clinic to redirect you. Right? That’s one example. Another is some of these physician- or provider-focused automation tools. I don’t know about you, but every time I’m documenting, I hate having to click even one extra button that I don’t have to, or opening a separate window. Again, that just introduces more complexity, not less. There are probably thousands of digital health companies out there nowadays that do not think about how they fit within your workflow on a day-to-day basis.
Kevin Pho: Yeah, so I think that health care is, of course, one of those fields where, paradoxically, when you add technology, it adds complexity, right? And you mentioned the electronic medical records—like I’m a primary care doctor. So that’s one of the fields where since the introduction of electronic medical records, it created a whole new field of scribes, right? To translate what we say in the exam room and put it in the electronic medical record system. And now with the advent of AI, you just have another layer where you have these AI scribes that can listen to us just so we can put that note in the electronic medical record. So it really illustrates how more technology actually adds to the complexity and, paradoxically, sometimes can make us less efficient.
Aiden Feng: Yeah, that’s true. But, you know, I think that’s a very broad statement, right? Both to what I said and what you said. I do think that there is a lot of potential. We shouldn’t be discouraged, right? And that’s actually why I still work in the technology space. That is because if we are grounded in what it’s actually like in the clinic, in the hospital, in the ER, and put physician or nurse or APP workflows at the forefront, and then design technology around that—take a patient-and-care-first approach—I go around, and I just got back from Vibe, and I heard many people saying, “Oh, hey, Epic-first this,” or “Oracle-first that.” I’m like, shouldn’t it be care-first or patient-first or even provider-first in terms of how we fit technology into care, not the other way around?
So I think that’s point number one. Point number two is the integration or the consolidation of so many of these point solutions into one single platform. And then number three, to what you were saying just now, is there is some really impressive technology out there with the large language models and the newest AI technology, but we need to really be thoughtful about how we apply that and how it fits into our care workflows today.
Kevin Pho: Thank you. So specifically, the emergency department, which is what your article was talking about—tell us about your vision to overcome some of the obstacles that you’re describing.
Aiden Feng: Well, actually, I didn’t even talk about what I do. So I’m still, you know, I’m a practicing anesthesiologist, but also, you know, as you can tell, I care a lot about digital health and the application of technology in health care. It’s been a learning experience over the past four to five years at a company called Fabric.
As much as I say, “Oh, hey, there are too many point solutions, and we need that integrated platform,” we actually started as a point solution in the emergency department. So, you know, to answer your question, over time, we started as, you know, the patient walks in the front door of the emergency department, we text the patient, set expectations, make sure they know what’s happening, what to expect, and then automate some of the data collection, right? If you broke your pinky, I have to ask you about everything from suicidal ideation to social determinants of health. So we automate some of that.
But what we quickly realized was that the ideal ER experience for patients is actually not to be in the ER, right? So I think that is where we need to start. In the ideal scenario, the lay consumer is sitting on the couch and trying to figure out what to do, where to go, and who to talk to. So how can we deploy technology in a way that reaches them at the top of the funnel and holds their hand through the journey of getting the right care at the right place via the right modality with the right provider? I think that is the opportunity. If it’s an uncomplicated UTI in a young woman, you can literally just do an asynchronous virtual visit and be done with it in 10 or 15 minutes, and you get a prescription in your box. But, you know, if you do need to go to the ER, let’s navigate you to the emergency department.
And once you’re there—so what I was talking about earlier—setting expectations but also leveraging technology to create virtual journeys in the ER. What I mean by that could be centralized virtual nurse triage or a virtual provider in triage to kick off the workflows, right? Instead of you waiting there, you have a centralized team of nurses and providers that can cover multiple ERs and multiple inpatient floors if needed, and then you’re freeing up resources on the ground to draw blood, to administer medications, and so on, to move things along.
Then you can even take that one step further to say we can actually create a whole virtual fast track of low-acuity chief complaints. You come in, and you get virtual nurse triage and virtual provider; they can actually just write the note, and off you go, right? We can talk about all the regulatory requirements in terms of EMTALA and whether a virtual exam counts as a medical screening exam or all those things, but based on our experience, you can definitely work through that and still bill for that visit and create a curated experience that is specific to your needs and your acuity level.
And let’s not forget, on the back end, before you leave, let’s make sure you get attached to a PCP and have a follow-up appointment scheduled. What boggles my mind is every time you get your teeth cleaned, before they take the bib off, they’re like, “Hey, let’s take a look at the calendar. When do you want to come back for your next cleaning six months from now?” Right? We can automate a lot of that right before you even leave the ER. Instead of giving you the paper, let’s give it to you via text and digitally, and then check in with you virtually through automated messaging after you leave—the next day, three days later. That is a consumer- or patient-first journey that I think we should be powering and moving toward.
And then the consequence of that on the provider side, on the nurse side, and on the hospital side is that it actually frees up capacity on the ground. Now, you can actually spend time focusing on the sickest patients, and so on. So that’s how we’re thinking about it.
Kevin Pho: So patients with low-acuity complaints will be seen by a virtual triage and, if handled—and if appropriate—can be managed and treated virtually without that patient setting foot into a physical emergency department. Is that what I’m hearing?
Aiden Feng: Well, that’d be ideal, but sometimes you need to go in person to get labs and get medications and so on, maybe outside of the four walls of the ER. We need to create accurate triage mechanisms to send people in who actually need to go in. So that takes care of people at home. And then once you’re there, I think you can actually power a completely virtual workflow within the emergency department itself with centralized labor resources that can be optimized across different sites.
Kevin Pho: We’re talking to Aiden Feng. He is a physician executive. Today’s KevinMD article is “Rising ER wait times signal larger health system challenges.” Aiden, let’s end with some take-home messages that you want to leave with the KevinMD audience.
Aiden Feng: Yeah, I think there are two OK points that we should take home, right? One is technology is currently not leveraged correctly in health care today. With the implementation of technology, we should be seeing productivity growth, capacity expansion, and experience improvement. I think at the core of that is we have been burdened with disjointed experiences from way too many digital health point solutions. It also has tremendous potential, as we know and see in other industries. If we are able to weave together one platform—one experience layer above the source of truth and the records in the EMR—we can actually curate and create personalized journeys and experiences for both patients and providers.
At the same time, we need to take an approach of deploying technology with a patient-first, provider-first approach, not a technology-first approach, right? To ensure that it actually creates efficiency and helps with workflows instead of creating additional complexity.
The second take-home point, I think, is as we think about the future and how we apply the latest AI technologies, we really need to, again, take a patient-first and quality-first approach in terms of doing it safely and responsibly. So I think, for lack of a better word, it’s a hybrid AI approach where if it’s an administrative question, yes, we can apply LLM models and deploy the latest technologies. But if it comes to clinical care, we should be careful and, you know, make sure that it’s grounded in evidence-based medicine and the latest guidelines, and hopefully, you know, at least for now, driven by deterministic decision trees and so on. At the end of the day, to combine those two points, it’s really about putting patients and care first. When you do that, you can also create downstream operational efficiencies and capacity expansion. Yeah, thanks for having me. It’s been great speaking with you today.
Kevin Pho: Aiden, thank you so much for sharing your perspective and insight, and thanks again for coming on the show.
Aiden Feng: Yeah. Thanks so much, Kevin.
