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Health care executives Susan L. Montminy and Marlene Icenhower discuss their article, “Solving a hidden challenge: 10 tips to reduce diagnostic error in the emergency department.” Susan and Marlene explore the complex, high-pressure nature of ED environments and the often-overlooked dangers of diagnostic error, which can result in severe injury or death. They offer 10 actionable strategies to improve diagnostic accuracy, such as using “working diagnoses,” implementing diagnostic timeouts, minimizing interruptions, and addressing cognitive biases. They emphasize the importance of fostering a collaborative team culture that normalizes diagnostic uncertainty and supports open communication to protect patients and support clinical decision-making.
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Transcript
Kevin Pho: All right, welcome to the show. Subscribe at KevinMD.com/podcast. Today, we welcome Susan Montminy and Marlene Icenhower. They’re both health care executives, and today’s KevinMD article is “Solving a hidden challenge: 10 tips to reduce diagnostic error in the emergency department.” Susan and Marlene, welcome to the show.
Marlene Icenhower: Thank you, Kevin. We’re so glad to be here.
Kevin Pho: All right. So, before we talk about the article, just brief introductions about what you do and who you are. So, Susan, why don’t you go first?
Susan L. Montminy: Sure, thank you. Well, I’m a nurse, and I have been for more than thirty years. As part of that, I also hold a doctorate in organizational change and leadership. And I share that because throughout that time, risk management and patient safety have always been a part of my job, even before it was a part of the actual formal job description. So, like many nurses, I began at the bedside in a hospital, very traditionally, and then began to move more into management roles. This is where I learned about the importance of teamwork, culture, and communication in patient safety. One of my management roles was an employee health manager, and that’s when the factors of emotional and physical health of each of the individuals that make up the care team became apparent to me as key. So, I share all of that because these experiences really combined positioned me well to now begin this formal phase of my career in risk management.
Most of those years were spent in a large multi-hospital academic health care system with a level 1 trauma center, and this really afforded me the opportunity to work with some extremely clinically complex cases. We were responsible for 24/7 support to our frontline providers. And I later came to be in my current position of director of risk management at an MPL company, and here is where I can share ideas such as what was in the KevinMD article about diagnostic risks in the ED to a broader audience.
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Kevin Pho: All right. And before we talk about the article, Marlene, just briefly introduce yourself and tell us a bit about your story.
Marlene Icenhower: Sure. So, I am currently a senior risk specialist at Coverys, a medical malpractice insurance company, and I work with our West Coast policyholders, helping them navigate some of the sometimes thorny issues that arise in their organizations. And I think Susan and I had a different path. I started my professional career as a nurse, like her, working at a teaching hospital. So, I spent a lot of time watching the constant cycling of residents and interns and students through there, which, as you can imagine, exposed me to a lot of mistakes. I saw a lot of mistakes, a lot of potential liability, which kind of piqued my interest in the whole issue of risk and liability. So, kind of on a lark, I went to law school, worked my way through as a nurse, and when I graduated, was desperately wanting to be a corporate lawyer, but much to my dismay, my medical background kind of pigeonholed me into medical malpractice. So, I took a job at a firm. It turned out that it was a really good fit for me, medical malpractice defense. And so, for years I tried cases in that arena and ended up here in risk management, which I found over the years that health care risk management really suits my skill set. So, like I said, I’m a risk specialist, and I work with policyholders.
Kevin Pho: All right. Both of you wrote the KevinMD article “Solving a hidden challenge: 10 tips to reduce diagnostic error in the emergency department.” Now, Susan, for those who didn’t get the chance to read that article, just tell us what it’s about.
Susan L. Montminy: Oh, sure. Well, first of all, the format of it is really focusing on 10 tips. We wanted to make it simple, a quick reference for those to bring into their organizations and talk through: Could this be a problem for us? Could these solutions work? How could we implement them? We understand how busy and how resources are stretched very, very thin in so many organizations for a myriad of reasons, which we could do a whole other podcast on, but the 10 tips was intended to be a simple, easy reference.
And how they came to be was basically because we do clinical claims analysis on areas that we feel are problematic, and we glean information from that clinical claims analysis to really target solutions on areas that, you know, really, to put it informally, are the biggest bang for your buck. If you don’t have a lot of time in your organization to focus on, you know, 40 things, let’s really talk about those things that are most likely to lead to error, which leads to harm. And of course, harm here is not just to the patient. It’s to their loved ones, it’s to the health care team that were involved in the error, and it’s emotional, the toll that it takes on everyone. And because I’m an MPL, you know, employee, it’s also, if anyone out there has been through, you know, the claim system, it’s physically and emotionally exhausting.
Kevin Pho: So, Susan, to follow up, and before we go into the tips, just give us a general sense of the scope of diagnostic error in the emergency department. Do we have any numbers or data just to kind of give us a sense of how big this problem is?
Susan L. Montminy: Yes, let me start really broadly, and I’m going to bring us back to, you know, 1999, because it’s that groundwork, “To Err Is Human.” You know, it was appreciated that in general, 98,000 Americans were dying from medical error. That’s what really spurred this whole patient safety movement. But it wasn’t until 2015, when “Improving Diagnosis in Health Care” was introduced, also by the Institute of Medicine, that they started placing emphasis on diagnostic error as a leading cause of general patient harm. Another really important statistic to speak to the scope of this problem was published years later in the British Medical Journal, where 795,000 Americans were either dying or becoming permanently disabled due to misdiagnosis each year. And then finally, our own data, that we looked back five years, showed that diagnostic error contributed to 26 percent of our medical malpractice claims and accounted for 41 percent of the indemnity paid.
And so, we broadened and looked at, well, what organizations are out there looking at this that are contributing to the conversation? And Leapfrog, Joint Commission, ARC, they’re all into this to look to minimize the risk. So, it’s what led us to say, well, what can we offer? What can we learn from our data and share? And again, which is what led to the KevinMD article on the ED diagnostic error.
Marlene Icenhower: I would also add that, you know, we spend a lot of time talking to health care organizations and providers about medical error and risk and claims. And, you know, a lot of times when you talk to folks, you feel like they really don’t have a good idea what’s generating claims in their organization. You know, they’ll point to things like falls and medication errors, which are those kinds of things that are really easy to spot. You know, they occur quickly, they’re dramatic, and so they’re easy to track and trend and work on. But the problem with diagnostic error is that it’s insidious. And so, you know, sometimes people get lost to follow-up, they don’t realize that they’ve been misdiagnosed for a couple of years. So, sometimes that feedback loop isn’t closed. So, you know, diagnostic error is hard to spot. And so, that’s one of the reasons that we did this paper, was to bring that topic to the forefront, get people talking about it because, you know, based on our data, it’s not the falls and the medication errors that are creating claims. It’s almost universally diagnostic error.
Kevin Pho: So, Marlene, give us, say, an example or a story of a typical diagnostic error in the emergency department that you’re finding through your claims. What would be a typical example of that?
Marlene Icenhower: Well, you know, a lot of our data shows that many of the diagnostic error cases are related to infection, right? So, you might have a patient coming in with vague symptoms, maybe abdominal symptoms, and because of the patient’s age, because of maybe the influence of diagnostic bias or intuitive bias, the right test might not be performed or the correct H&P might not be performed. They don’t gather enough information, gather inappropriate information, and the patient leaves with maybe a diagnosis of UTI when in fact it might be an abscess or something like that. So, I mean, that’s the typical case that we see in the ED.
Kevin Pho: And when you mentioned intuitive bias, Marlene, what exactly is that?
Marlene Icenhower: Yeah, that’s a really, really interesting topic. It’s one of my special interests. So, we also refer to it as cognitive bias. In cognitive bias, intuitive thinking has a huge role in the diagnostic process. And it sounds like such a negative thing. Nobody wants to be biased, but it’s a really natural way of decision-making. We all use bias to make quick decisions in everyday life, from what coffee to drink to what clothes to wear. You know, if every decision required a scientific analysis, you wouldn’t get a whole lot done. And that’s true with diagnosticians, right? They engage, especially in high-pressure environments like the ED, they engage in intuitive shortcuts all the time to arrive at diagnoses, and those are based on context, maybe past experience. I’ve heard a lot of physicians talk about how they think in terms of probability, and these intuitive shortcuts or these biases don’t always serve them well.
But the thing about cognitive bias is that it takes place in less than an instant, and most of the time it happens subconsciously. So, an example of cognitive bias is maybe a patient who was, you know, young, who comes in with, let’s say, rectal bleeding. One wouldn’t automatically leap to the conclusion of colon cancer, right? Based on past experience, probability, the most likely thing is a hemorrhoid or something like that. So, that’s a form of cognitive bias based on the patient’s age and presentation that leads you to make a leap in decision-making that may not always turn out to be correct.
Kevin Pho: And before we get back to Susan, I just want to kind of close the loop in terms of the practice setting in the emergency department. So, we always think that the emergency department’s a high-pressure setting that’s only getting worse with things like staff cuts and all that. So, in general, what are some specific things in the emergency department that would make that setting prone to diagnostic error?
Marlene Icenhower: Yeah, so from my perspective, you know, the ED is obviously a chaotic environment, and in those kinds of environments where there’s lots of activity, lots of busyness, there’s tons of opportunity for interruption and distraction for the providers. Every time a provider is interrupted in the middle of a task, there’s a chance for an error, right? So, you might forget to return a phone call, you might forget to make a note, you might forget to enter an order. So, the potential for interruption in those high-activity environments increases, and every time it increases, so does the potential for error. So, we’re always, and Susan can attest to this, we’re always coaching organizations to look for ways to reduce distractions and interruptions as part of the risk management efforts, especially in places like the ED, where interruptions are so common.
Susan L. Montminy: It’s also that most of the patients are brand new to everyone. It’s not an established patient where I understand their history, I know other things that are going on with them. And so, you’ve got to make this snapshot decision based on a blank slate. I mean, you’re really reliant on what’s in front of you. And when a patient has an acute situation and they enter the door of the emergency department and they’re there, say, for several hours, during those hours, things could be rapidly changing, requiring the physician to continually reassess and assess the diagnosis before the patient then exits the emergency department with not only their diagnosis, but their treatment.
And, you know, I love that example, Marlene, you gave earlier about infections and, you know, things that our data revealed were happening. But also, Kevin, it was orthopedic-type situations where a fracture was missed, or, you know, the X-ray, you know, had a preliminary read, you know, and that’s what the diagnosis was based on, and then an after-read showed something different. So, I really think that’s unique to the emergency department as well.
Kevin Pho: So, Susan, your article, you and Marlene’s article, focuses on ways that we can overcome these diagnostic errors. So, what are some of the main tips that you can share with us?
Susan L. Montminy: Well, I’ll just build on what Marlene talked about with bias. Let’s name it. Let’s not be afraid of it. Let’s not think of it as a bad word. Let’s ask the question: “OK, something is puzzling me here. These pieces of information are not making sense. They’re not connecting. Is bias at play here?” Really feeling comfortable with uncertainty, if you could put it in that way.
And also, you know, I really think that, you know, we talk about team sport. Health care is a team sport. And so, one of the tips that we put forward is that diagnosis should also be a team sport. If the physician is in a place where, you know, they’re really either just puzzled in general or perhaps a treatment that was started is not achieving the result that they thought the treatment was going to achieve, have a huddle. Bring people together and say, “All right, what am I missing? What’s going on? What other thoughts do you have?” So, those are two main ones. I mean, I could go on, but I want to pause a moment to see if you have any follow-up questions on those.
Marlene Icenhower: What Susan’s describing is what we call a diagnostic timeout, right? Just like in surgery, where they have a moment of cool reflection and a team opportunity to discuss. So, we encourage folks to establish a process for a diagnostic timeout, and also to build into that process triggers for the process, like, you know, return visits, requests for refills, symptoms that don’t get better. All of those things should alert you to maybe your diagnosis is incorrect.
Kevin Pho: So, Marley, what exactly would that look like? Tell us a scenario using some of these techniques. It could be the diagnostic timeout. So, from a clinician standpoint, what exactly would that look like in an emergency department setting?
Marlene Icenhower: Yeah, so it would look just very similar to a surgical timeout, right? When there’s a puzzling case, when something, you know, there’s a misalignment between symptomatology and test results or radiology, you gather the members of the team, either by telephone or in person, gather at a particular place, in a quiet place, and you just examine. You go around the room. Have we missed anything? Do these symptoms align with these test results? What are we missing? You know, kind of that thing that shows up on TV a lot, you know, like House, right? What are we missing? That kind of a process.
Susan L. Montminy: Yeah, and again, it’s really important not just to do it, but to identify triggers for that process. And if I could just go back to, you know, earlier, Marlene talked about diagnosis is sometimes insidious. It’s not like a fall. It’s really encouraging reporting misdiagnosis as events and treating them in the same way. Why are we doing that? So we can learn what happened. Was there a gap? Was there a vulnerability that we can then create a system around? I mean, proactively are some of the things that we shared, but you can also learn retrospectively. What could we have made easier in place of a system?
And I often go to the electronic health record because, you know, best practice is always, you know, speaking with your fellow clinicians in real time, but sometimes, let’s face it, especially in the ED, where things are moving fast, communication most often is, I’m looking in the electronic health record. So, here is where design is really important for the person trying to make the diagnosis to have a clean view of these disparate pieces of information that would really lend itself to helping to arrive at the correct and accurate diagnosis. And leaders play a really big role in this, to have their IT specialist, their quality specialist, and a physician sit with me. Follow me around for a shift. And what does my box screen look like? Does it pull in artificial intelligence-wise? Does it pull in what I need in that moment to help me in this fast-paced environment?
Kevin Pho: So, Marley, I’m going to ask for a success story. So, what would be an example where you implemented some of these changes in a typical case and really moved the needle when it comes to decreasing the incidence of diagnostic errors?
Marlene Icenhower: Well, I think, you know, the success story that I would envision, that I would hope that we would see a lot, is the situation where there’s an ambiguous or a foggy diagnosis that the provider communicates that uncertainty. You know, we’re kind of moving away from this whole idea that providers have to have diagnostic certainty and can’t communicate uncertainty. But where they communicate and convey that diagnostic uncertainty, where other members of the team, perhaps other disciplines, other nurses, you know, other roles, come in, discuss the case, and they maybe identify some sort of cognitive bias that was skewing their reasoning, and come up with the correct diagnosis. And then, for the cherry on the top, maybe the organization studies that and looks at the way that they were able to avert harm from reaching the patient, kind of like a success cause analysis, and celebrate when things go right, not necessarily when things go bad. So, I think there’s a lot of techniques that you can build into your everyday workflows that can set you up for success rather than failure. And it’s, you know, another example of a systems issue, process issue.
Kevin Pho: We’re talking to Susan Montminy and Marlene Icenhower. They’re both health care executives, and today’s KevinMD article is “Solving a hidden challenge: 10 tips to reduce diagnostic error in the emergency department.” Now, I’m just going to end with some take-home messages that you want to leave with the KevinMD audience. Susan, why don’t you go first?
Susan L. Montminy: Sure, thank you. Really take the 10 tips, have a conversation in your department, and if you want to go further, there is a white paper associated with it that also has a self-assessment that you can bring into your emergency department to further identify some vulnerabilities, compare it with your own data. Take our data, and take the data that you have at your fingertips in your organization, and focus your efforts to reduce risk. It really does harm so many people when there’s a diagnostic error.
Kevin Pho: And Marlene, what are your final take-home messages that you want to leave?
Marlene Icenhower: Yeah, I think I would tell folks that it’s OK to be unsure as a diagnostician, at least to be unsure, and to communicate that uncertainty to the team and to the patient, and also be sure that you’re aware of the possibility of cognitive or diagnostic bias and how it plays a role in diagnostic error.
Kevin Pho: Susan and Marlene, thank you so much for sharing your perspective and insight, and thanks again for coming on the show.
Susan L. Montminy: Our pleasure.
Marlene Icenhower: Thanks.
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