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- 00:00 Introduction
- 03:33 Mental Health & Wellbeing
- 06:43 Case 1
- 11:48 Exercise 1
- 12:53 Exercise 2
- 14:35 Case 2
- 19:15 Exercise 3
21:22 Exercise 4
23:24 Case 3
27:29 Exercise 5
28:07 Exercise 6
- When evaluating a struggling learner, first ensure their challenges are not due to an unmet need related to mental well-being, their personal life, or a problematic learning environment. According to one study, around 40% of struggling learners are grappling with an underlying mental wellbeing issue, frequently anxiety, depression, or ADHD.
- Mental health screening both helps residents seek appropriate treatment from their program’s designated mental health professional, and better enables them to progress with clinical coaching.
- Second, perform a “global assessment” to identify the domain(s) that are contributing most to the learner’s difficult.
- Review standardized assessments and observe the learner directly, evaluating them across four domains:
- Medical knowledge
- Clinical reasoning
- Organization & efficiency
- Professionalism & communication
- Although most struggling learners are presumed to have medical knowledge deficits, the most common primary deficits are in clinical reasoning and organization & efficiency.
- Initial feedback to residents should be “low-inference,” focused on concrete observations / behaviors, rather than “high-inference,” which includes conclusions about those behaviors.
- Review standardized assessments and observe the learner directly, evaluating them across four domains:
- Third, for learners who seem to be struggling somewhere along the clinical reasoning pathway, try to identify which step the learner is struggling with the most
- Steps for clinical reasoning (Cavet: in practice, this is an iterative process):
- Generate hypotheses → gather data → create a problem representation → refine hypotheses → select a working diagnosis
- Steps for clinical reasoning (Cavet: in practice, this is an iterative process):
- Case 1: Hypothesis-driven data gathering
- Definition: using diagnostic hypotheses to keep obtained information focused and appropriately thorough, which improves diagnostic accuracy.
- Possible manifestations of deficit: Excessive or indiscriminate collection, reporting, and/or documentation of information (which may appear as disorganization and inefficiency); Alternately, absence of relevant data gathering despite appropriate knowledge base.
- Coaching Exercise 1, “Searching for the scripts”:
- Provide the learner a chief complaint, ask them for a tiered differential, then ask them to choose only five pieces of historical information and five physical exam findings to distinguish between the diagnoses they’re considering (Parsons et al, 2020).
- Coaching Exercise 2, “Findings That Matter” AKA highlighting key features:
- Provide the learner a printed history and physical and ask them to highlight only the information they believe is most relevant for building and narrowing their differential.
- Case 2: Problem representation
- Definition: creating a “one-liner” that effectively pulls all the most relevant information together and drives the differential diagnosis (e.g. by triggering appropriate illness scripts).
- Possible manifestations of deficit: Struggling with multiple forms of clinician communication (e.g. handoffs, consults, oral presentations) and appearing to “miss the big picture”
- Coaching Exercise 3, “Problem Representation Breakdown”:
- Deconstruct the problem representation into its three primary components– patient demographics and risk factors, temporal pattern expressed using semantic qualifiers, and key symptoms and findings.
- Coaching Exercise 4, “Role Reversal”:
- Ask the learner to role play as a new patient presenting with a common condition, through which they may reveal features of their illness script for that disease.
- Case 3: Hypothesis generation
- Definition: the ability to generate a wide differential based on limited information.
- Possible manifestations of deficit: narrow differential diagnoses, delayed response to new concerns, or acting inappropriately during time-sensitive scenarios like codes.
- Coaching Exercise 5, “Triage”:
- Ask the learner to assign an urgency level, from 1 to 10, to all the patients on their list or all the calls they received in a given day.
- Coaching Exercise 6, “Scaffolding”:
- Encourage the learner to develop frameworks for common and uncommon chief complaints using physiology, epidemiology, severity, etc.
Andrew: I think that everybody struggles at some point along the way, and we all specifically struggle with clinical reasoning, again, because the system is not set up to explicitly teach it along the way. And so we’re all left on our own to some degree to learn it, and so we learn it at a different trajectory.
Jess: The voice you heard is Dr. Andrew Parsons, a hospitalist at UVA and Chair of the COACH program’s Clinical Reasoning Subcommittee which helps support residents who are struggling with clinical performance. I’m Dr. Jess Dreicer, also a hospitalist at UVA School of Medicine, a long-time fan of the pod making my Core IM debut.
Zaven: And I’m Dr. Zaven Sargsyan, a hospitalist at Baylor College of Medicine in Houston. Also a long-time listener and first-time co-host, and very excited about this important topic. What Dr. Parsons said makes so much sense – I don’t remember learning much about clinical reasoning in medical school. And now as an educator, I definitely struggle with assessing it, cause you’re trying to understand how someone else is thinking, but all you hear is the product of the thought process.
Jess: And so on this episode of Hoofbeats, we’ll focus on building a differential, so to speak, about what might be going on with a learner who is underperforming clinically. We will work through 3 learner cases and explore helpful strategies to try improve weak areas.
Zaven: And I think this episode is going to be really useful for anyone working with learners, as Hoofbeats listeners, we’re really used to hearing expert diagnosticians seamlessly go through the clinical reasoning process, but we don’t spend as much time focusing on examples of when this process isn’t going well.
Andrew: You get a lot of vague phrases like “they don’t seem to be putting it all together,” or “they don’t see the forest for the trees,” or “they can’t really make decisions on the fly,” things like that. You know, that alerts you that it may be a clinical reasoning issue.
Zaven: I’ve definitely said vague phrases like that… Like, sensing that something other than knowledge is off but not having the language to pinpoint what it is or how to address it.
Karen: I would say that the most common reason that people are referred is that there’s a medical knowledge deficit, or that the learner needs to read more. What’s interesting is if you look at these learners, at least in my experience, uh, medical knowledge is not the most common issue. It’s just something that we know how to describe and something that we’re familiar giving feedback on.
Jess: That’s Dr. Karen Warburton, a transplant nephrologist at UVA and Chair of the COACH program. And I’ve definitely been this person too when I don’t know what’s going on with a learner who’s struggling and I often fall back on the common habit of telling them that they should “read more.”
Karen: If I looked across the board at all struggling learners that I’ve worked with, I would say most of them have what I would call average funds of knowledge, and really, for most graduate medical learners, it comes down to how they apply that knowledge. And I think that is a distinction that many evaluators don’t know how to make. They probably get it, but they don’t have the language to describe it, and so they just default to knowledge.
Jess: So it sounds like there is a lot of room for improvement here.
Mental Health & Wellbeing
Zaven: Before we start nerding out about different learner phenotypes and coaching exercises… let’s talk about some can’t-miss issues that are often overlooked. Namely, we have to check in with our learners about their mental well-being. Like hey how are you feeling? How’s the month going? … or How are things outside of work, cause a lot of social circumstances and stressors can also influence performance …
Karen: There is tremendous overlap between mental wellbeing issues and clinical performance struggles. I would say that about 40% of learners who are struggling have some underlying mental wellbeing issue. And in our cohort, anxiety is the most common, followed by depression, followed by cognitive issues in our cohort– most commonly ADHD that was either undiagnosed or, more commonly, was known about but was not being properly treated.
Jess: So, the take away here is when you are working with a team member that may not be up to par in their clinical performance, the first task is to consider mental health issues that might be at play–we just can’t miss that. Also consider other cognitive demands such as family responsibilities or financial difficulties that might be affecting them.
Zaven: OK – so if we’re fairly confident that mental health issues aren’t playing a major part, what else might be going on?
Karen: The way that we categorize deficits is not strictly by ACGME competency, but we group them into medical knowledge, clinical reasoning, organization and efficiency, and then professionalism and communication. And for our cohort of graduate medical learners, clinical reasoning and organization and efficiency are probably the most common, followed by professionalism, followed by medical knowledge.
Zaven: Alright, so before we delve more specifically into struggles with clinical reasoning, it’s probably helpful to first understand what components make up clinical reasoning normally. Then when you’re working with a learner, you can try to read between the lines and make an informed guess about which part of that process might be off.
Andrew: Beginning with chief complaint, it’s hypothesis generation to hypothesis-driven data gathering, then problem representation, refining hypotheses, and then selecting your illness script as your working diagnosis.
Zaven: So as soon as you hear the chief complaint you should already be forming some diagnostic ideas, what Dr. Parsons called hypotheses… and then it’s sort of an iterative process of gathering more data in a purposeful way, then filtering that data more into a problem representation, and then refining those hypotheses further from there.
Jess: Right. And although breaking it down into linear steps like that is really necessary to a discussion on clinical reasoning, in reality it’s such a non-linear and complicated process.
Zaven: With that, let’s hear our 1st learner case from Aaron Troy, MS4 at NYU. And while you’re listening, pause and reflect if you recognize some of these traits in a learner you’ve worked with, and how you might begin to offer them feedback.
Case 1: Data Gathering
Aaron: It’s your first day on the teaching service and JP, the intern on the team is presenting the first patient. He appears extremely anxious. His presentation is quite disorganized and does not follow the typical H&P format, or any structure really. He speaks for 15 minutes and has not even gotten to the physical exam when you interrupt him and move the team along to the assessment and plan.
Afterwards you pull the senior resident into the hall and ask him how it’s been going with JP. He says that he’s a hard worker, arrives at least an hour before everyone else and is the last one to leave for the day. However, despite being the first one and carrying fewer patients than the other intern, he still barely has time to see all of his patients before rounds start. You check in with the program director to see if there were any concerns about JP’s academic performance in medical school and she tells you that there were no concerns and in fact, he had a strong academic performance in medical school.
Jess: Before we hear our expert’s assessment. Take a moment to reflect, what do you think might be going on with JP?
Andrew: You have a relatively inexperienced intern that did well in medical school and performed extremely well on their standardized tests struggling to be efficient and organized in multiple activities throughout the day.
Zaven: Oof, I get antsy any time I hear that word efficiency or that word comes to mind, just because it’s such a vague loaded term. There’s this framework I like for feedback, which is to think of feedback statements as “low-inference” versus “high-inference.” Low-inference meaning that you’re just describing what you see about the trainee, whereas high-inference is you’re drawing conclusions. And in general, feedback should be more “low-inference.” Like it’s not helpful to tell a student “you’re disinterested,” because there’s a lot of inference there, and thus it may not be true.
Jess: Yeah, I feel like a typical learner’s immediate reaction to that would be “No I’m not!” And they would shut down the conversation.
Zaven: Yeah, I would totally just freak out if I heard that from my attending. But if you give more low-inference feedback, like “I noticed that your arms are always crossed, you tend to sigh loudly, and you rarely ask any questions,” that’s factual, and you’re at least starting from common ground.
Jess: So how do we apply that to efficiency? If you tell a learner “you’re inefficient” is that high or low inference?
Zaven: Well I think it’s a little high inference because it’s not an actual describable behavior… it’s kind of a blanket statement based on your gestalt.
Jess: What about “you presented a 5-minute physical exam, which is too long…” That would be low-inference, right?
Zaven: That’s definitely much better, at least identifies the specific behavior. But it still doesn’t tell you how to fix it. So once you identify the actual behavior, now you still have to explore why it’s occurring, cause it could still be for a number of reasons.
Andrew: One of the interesting things about deficits in clinical reasoning is that they can manifest in a number of different behaviors and, through my experience doing remediation coaching, I’ve been able to group those different behaviors into some common phenotypes. And so, the phenotype you described here is largely someone that sounds disorganized and lacks efficiency in everything they do.
Jess: So we may also might see someone like this reading every. single. lab. value, or going off on a tangent about the patient’s bunions when they’re here for diverticulitis or a painfully thorough sensory exam in a patient coming in with chest pain.
Andrew: They are likely able to generate a differential diagnosis based on the chief complaint, but it sounds like, because they’re largely inefficient and in what they do throughout the day, that the next step, the gathering a history or gathering a physical exam, is not organized. The fact that they’re taking so long, not only in the room with the patient, but also when they’re describing their history, and also when they’re pre-rounding and having to pick out data from the electronic medical record–the fact that they’re not picking out relevant pieces of information but, instead, seem to be just presenting numerous pieces of information–points to the fact that they may not be practicing hypothesis-driven data gathering.
Zaven: So let me process this for a second. Hypothesis… driven… data gathering. So the idea is that even as you’re doing your history and exam, and reviewing the labs… if you have specific diagnostic hypotheses in mind, the data gathering will be more focused and relevant… and thus more efficient too. Is there a way to practice or coach this skill more preemptively?
Exercise 1: Searching for the scripts
Andrew: So there’s one exercise called “searching for the scripts.” And so I would give just a small piece of information, let’s say “a 45 year old male with chest pain.” Okay. “Give me three diagnoses on a differential, prioritized.” And I think they would be able to do that quite easily cause they’re common diagnoses and they have good medical knowledge. Okay, but with that differential, you’re only allowed five pieces of historical information and five physical exam findings to determine the diagnosis. And this really pushes them to prioritize their data gathering and make it most relevant. So they need to know what are truly the distinguishing features of the history and the physical exam that allow them to distinguish between the diagnoses that they have on their differential.
Zaven: Ooh that’s good. I feel like we often tell learners that they should present quote unquote “just present the relevant stuff..” but what if they don’t know what relevant stuff is? What Dr. Parsons described is a great way to practice hypothesis driven data-gathering.
Exercise 2: Highlighting key features/co-selection
Andrew: Another exercise you can do is called highlighting key features. And in this exercise, you can print out full history and physicals unfamiliar to the resident, put them in front of them, give them a highlighter and ask them to read top-down the history and physical and highlight key features of history and physical exam as they go. This forces them to do something called co-selection, which is what we do when we’re interviewing a patient routinely which is, as we’re gathering information, we’re reprioritizing the differential in our mind, and then adjusting the data that we want to gather. So what you would like to see if somebody is doing this well is they will highlight certain things, but then as the differential diagnosis changes in their mind, they may say, “no, that piece of data is not relevant anymore,” or go back up and say, “actually this piece of data is now more relevant.” And so they should constantly be adjusting the features that they find most salient.
Zaven: Very cool. So for a patient coming in with fever and cough, their history of hot tub use and pet birds might seem really interesting and relevant at the beginning, but once their influenza test comes back and it’s positive you can probably de-prioritize some of those details.
Jess: Nice. So, to summarize the take-aways from case 1… sometimes what looks like “inefficiency” and not being able to prioritize is actually a clinical reasoning problem… in particular a struggle with hypothesis-driven data gathering, which is prioritizing information relevant to the problem at hand.
Case 2: Problem Representation
Aaron: At the end of rotation feedback, you are talking to your resident, Ayanna about the intern, Tom. Ayanna says that she and some of the other residents have been talking about how Tom is really inefficient at giving handoffs to the night-team, it takes him almost twice as long as the other interns. And yesterday he called a relatively simple cardiology consult about an older man with cardiac risk factors presenting with chest pressure and spent nearly five minutes explaining the question. Ayanna says she feels like Tom “just doesn’t seem to get the big picture.”
Jess: Ok. Well I see some similarities here with organization and efficiency, but I’m guessing there’s an issue with clinical reasoning here too… after all, this is a Hoofbeats episode about clinical reasoning.
Zaven: That’s some solid clinical reasoning there Jess.
Jess: Thanks Zaven.
Zaven: Let’s take a moment to think then, where might the problem be along the reasoning pathway?
Andrew: You might be tempted to say, I think, when you hear this case, that well, again, this is another organization and efficiency issue, because this is another resident that’s taking too long to do the standard activities that are in their clinical day. But there’s some key differences here.
This is a resident that appears to struggle with multiple forms of clinician to clinician communication, such as giving a handoff, calling a consult, and perhaps oral presentations, all of which require accurate and concise problem representation. And they also seem, or are told by their evaluators, that they tend to miss the big picture.
Zaven: Interesting, so the difference is that, in the first case, they were struggling to prioritize in the information-gathering stage, but this learner isn’t managing existing information well, like when it’s time to put it all together.
Jess: Yeah it sounds to me like this learner is struggling with problem representation which, you may remember, is when you put together the key aspects of the case: patient’s risk factors, key presenting symptoms with their time course, and the most pertinent findings so far.
Karen: The problem representation really requires that you understand what’s going on with the patient and that you’re able to pull together a lot of information and very succinctly.
Andrew: Problem representation is basically a fancy term for the one liner. So it should be an accurate and concise, up-to-date, one liner that allows the listener to trigger their illness scripts that have stored knowledge that they have, and it allows the diagnostician to refine their hypotheses that they originally came up with. And it’s an essential skill for any communication.
Karen: It’s a skill that’s critical for us to learn, to be able to do so many of the things that we all do in our sleep. So it’s critical for handoffs. It’s critical for calling consults. It’s critical when you’re an attending and have 25 patients on your list.
Jess: Alright, I think what she’s saying here is that it’s pretty critical. Clues that your learner might be struggling with problem representation include issues with communication that requires a one liner, that would be like calling a consults and handoffs and, in addition, struggles with the off-the-cuff summary statements at the end of rounds.
Zaven: That’s super helpful, and I’m always gonna keep it in mind. By the way, this is a bit of an aside, but there’s this quote I like by Charles Kettering: “A problem well-stated is a problem half-solved.”
Jess: Nice, I love that.
Zaven: Yeah, and I think it can really explain why issues with problem representation would present with inefficiency, even outside of this context of calling consults or doing handoffs. So for example, say your problem representation is a young person with acute dyspnea and hypoxemia and a super clear chest X-ray. That X-ray being clear really limits or narrows the differential. But if you don’t include in the problem representation as an important feature of the current scenario, suddenly you’ve mentally backtracked. You’re not as far along in narrowing the differential.
Jess: I think that’s a great example of how what you include in the problem representation being critical in the next steps in your thinking. So once we identify issues around problem representations, how can we help support this learner?
Exercise 3: Problem Representation Breakdown
Andrew: Yeah, so I think the first thing you have to do is you have to break down the problem representation into its concrete steps and explicitly teach it to them. So for me, a problem representation has three components: First, who is the patient? What are the demographics and risk and risk factors? Secondly, what is the temporal pattern of the illness? And in this case, you want to use semantic qualifiers, which are these opposing descriptors or medical terms. You’re taking the patient’s words and changing it into your own medical terms. And then third are what are the key signs and symptoms.
Jess: I’m going to be honest, it took me a long time to wrap my brain around what is a semantic qualifier.
Zaven: Same here. I feel like I used that term just to sound smart for a long time and I could never actually define it. But when I’ve tried, I think of them as brief, medically meaningful descriptors. Like taking the fact the pain started this morning and calling it acute, or hearing that it lasted two hours then came back later, then went away and came back again, and calling it intermittent.
Jess: Right. Semantic qualifiers help you more easily categorize or compare and contrast clinical features like acute vs. chronic, symmetric vs. unilateral…
Andrew: And so that basic structure should allow the resident to practice actually writing down problem representations on their patients at multiple times throughout the day.
Jess: So, to walk through this exercise, I would sit down with the trainee in the morning and they’d say “this is a 67 year-old man with type 2 DM and significant smoking history who presents with acute typical chest pain.” And in the afternoon, after the cath, stent placement and echo results came back, I’d expect them to say something a little bit different, like “A 67-year old man with risk factors for CAD who came in with typical chest pain, was found to have CAD and new ischemic heart failure.”
Exercise 4: Role reversal
Andrew: Another thing I like to do is kind of a role play exercise, where you actually ask the resident to take on the role of a patient. So if we were to take a diagnosis, let’s say of a new brain tumor/brain malignancy that’s causing increased intracranial pressure. And let’s say you’re a 30 year old female, and you’re presenting to clinic with this new finding. How do you convince the doctor that you’re going to see that that’s truly what you have? And so you take on that role play and the resident should be forced to tell you, for instance, that they have a new onset headache, and they’ve never had headaches before, that it’s worse in the morning, that it’s associated with nausea and vomiting, and that it’s quite severe. And you’re forcing the resident to basically do the problem representation based on a basic illness script for increased intracranial pressure due to a brain mass. And so that’s a little bit more focused on illness script, but illness scripts and problem representations go hand in hand. And so that’s a great way to, to practice.
Jess: When learners hear you suggest “role-playing exercises,” you’re probably going to get some eye rolls, but I do think that actually sounds like a helpful exercise.
Zaven: So taking a step back and looking at these two cases, it seems like a lot of where learners struggle is filtering signal from noise, stuff that’s important from what’s not. The problem in the first case was hypothesis-driven data gathering – being thoughtful about which information is important to gather and not wasting time early on noise, stuff that isn’t relevant… and in the second case about problem representation, it was all about filtering at a later stage, once you had all the data in front of you – and highlighting the brightest signals to best conceptualize the case for yourself and your colleagues…
Jess: Alright, with that, lets move on to our last case.
Case 3: Hypothesis Generation
Aaron: You get an email from your colleague, Dr. A before rotating onto a two week teaching service. She warns you that the intern on the team, Seth, sometimes acts “unprofessional.” He got extremely frustrated every time his pager went off. He did not call the most important consult discussed on rounds until after 2PM and one of the nurses found me to ask if I could put orders for them because Seth was not responding to her repeated concerns for patients. We had a rapid response one day and he just stood there staring at the monitor, and the nurse asked a question and he said ‘yea whatever you think’.
Jess: What might be going on with Seth? How might you start to approach him? Is there other information you would want?
Karen: It sounds like this is someone, if I’m getting everything, who is, kind of, there’s a delay in response and maybe lack of recognition when things are important. I think there’s a huge differential here. And I think the first thing I would do is talk to the resident and ask what’s their perception of things? And I certainly would be concerned about mental health.
Zaven: Dr. Warburton gives us an important reminder to check in about well-being. But the other thing I might think about a resident who’s not responding to pages or recognizing important changes is that they’re disorganized or forgetful. And I can totally see myself sitting down with Seth and talking about their system of to-dos and check boxes… But if those things check out fine, what else could be going on?
Andrew: I’ve worked with a resident exactly like this and, for months actually, it was felt that he was unprofessional. Though it caused quite confusion because every time somebody met with him one-on-one he was quite personable and didn’t give any red flags that he would be unprofessional. And I actually think, in my experience, this is a problem with hypothesis generation because when faced with urgent situations like the rapid response, or situations where the resident’s unable to sit down and really take their time and think through things in a very analytical way, they really struggle. Again, this goes back to the fact that if this resident has average to above average medical knowledge, they probably did quite well in medical school or even on standardized tests with prompting. But in more urgent situations, there’s no prompting and there’s even limited history and physical exam and they’re pushed to make decisions.
The ability to generate a wide differential based on very limited information is, kind of, the hallmark of effective hypothesis generation, the first step of clinical reasoning pathway, and is very important for seeing new unfamiliar patients in high acuity situations.
Zaven: It makes so much sense that difficulties with hypothesis generation would lead to an appearance that resident isn’t responsive enough or isn’t doing their job… And that’s I’d never considered before! The other thing I can imagine would have that appearance is difficulty with making treatment decisions, what some people call ‘management reasoning.’ This is especially difficult under diagnostic uncertainty like in a rapid response, or when you’re getting paged back to back with new concerns. And, I have to say, I actually had trouble with this my intern year. Nurses would often get frustrated with me and I could tell cause I was really slow at making decisions and prioritizing… but now I wonder if they saw me as unprofessional.
Jess: Zaven, I really appreciate you sharing that with us. I think that’s inspiring to hear an amazing clinician like yourself talk about a struggle with aspects of clinical reasoning. And I think it’s certainly true that an assumption of “unprofessional behavior” might be unfairly made in a case like that. If we do figure out it’s a problem with prioritization, hypothesis-generation, or decision-making… what can we do to help?
Exercise 5: Triage
Karen: Another exercise has the resident create a “top five” to do list every three hours ordered by priority. So this is a model that an intern is getting calls all the time, the to do list is constantly growing and things are changing. And so the focus here is on reprioritizing problems as issues arise throughout the day. And the idea is that the intern would review this list several times during the day with a coach who can provide real time feedback on the list and assignment.
Jess: Sounds like a fancy version of “run the list,” with a bit more explicit talk of how to prioritize. What else can we do to improve hypothesis generation?
Exercise 6: Scaffolding
Andrew: If a resident struggles to generate hypotheses, I would really focus in on giving them a framework, or multiple frameworks, to generate a broad differential based on limited information. So some commonly used frameworks would be an anatomical framework, or an organ system based framework, or a focus on epidemiology or “what’s the base rate?,” “common things being common,” or “can’t miss diagnoses” is another example.
Jess: It’s so helpful to have a framework to fall back on in a crunch. “Ok what can I not miss here?” “What’s common?” or even thinking anatomically “what’s in the right upper quadrant that could be hurting?”
Zaven: Yeah, those frameworks are critical when you have to make decisions on the spot, like in a rapid response or at two o’clock in the morning.
Andrew: Kind of like, what’s a framework for making management decisions? So if you were to say like, what management decisions do we commonly make, like labs, imaging procedures, calling consults, medications and monitoring. So if you took those six things and you said, okay, fill out this framework for a given syndrome.
Jess: Alright, I learned a ton… Let’s hit some take-home points:
Zaven: First, always consider whether there’s a mental well-being issue. Anxiety and lack of psychological safety are very common, but personal issues, physical illness, or cognitive barriers can also be in play.
Jess: I’m walking away with the new ability to think beyond medical knowledge deficits when evaluating a learner who’s clinically underperforming. Next time, I’m going to consider clinical reasoning, organization and efficiency, and professionalism and communication.
Zaven: Within clinical reasoning, I learned that it’s not all one thing – there are different components of it where we can falter, like poor filtering at the data gathering stage, poor problem representation, hypothesis generation, or treatment decisions. And how, surprisingly, at least to me, those deficiencies can present with an appearance of disorganization, inefficiency– and even unprofessionalism.
Jess: When I have a learner who needs some more work in the data gathering domain, I’ll have some exercises to pull out like searching the scripts, where I’ll have them choose only five questions to differentiate between three diagnoses; or highlighting key features in an H&P as they’re thinking through their working hypotheses.
Zaven: If I see someone’s having trouble with problem representation, I’ll break down the three components of that process, which are: 1. Key demographics/risk factors 2. Temporal pattern of illness along with other semantic qualifiers, and 3. Key symptoms and findings.” And to help them see the connection between PR and illness scripts, you can do a role play exercise where the learner acts as a patient with a particular disease, and makes sure to include those 3 key components as they represent that patient.
Jess: Finally, for a learner struggling with hypothesis generation, I’ll help them develop some frameworks to apply in that process, like anatomic or physiologic approaches, or teach them to ask both what’s common AND what diagnoses can’t I miss? I might also have them practice their triage skills by creating and then re-creating their list of top five priorities for the patients on the floor every few hours.
Karen: And we ought to be teaching more deliberately, these clinical reasoning skills and not assuming that everybody comes to residency already knowing how to do a problem representation or to gather data effectively in a compressed timeframe. So I think ultimately the things that we’re doing in a coaching program should become part of mainstream education.
Jess: I hope that all educators walk away from the podcast thinking about how to utilize these exercises proactively, like during noon report or didactics and not only as an afterthought when we notice someone is under-performing. Okay, and with that said I think I’m ready… alright I’m gonna do it… I promise that never again will I just write “read more” on a learners’ evaluation.
Zaven: I believe in you Jess. I don’t know if I can promise the same, but I’ll read more less. If you found this episode helpful, please share with your team and colleagues and give it a rating on Apple podcasts or whatever podcast app you use! It really does help people find us.
Jess: If you want to add any of your own tips or share challenges, tweet at us and leave a comment on our website, on instagram or facebook page. Thank you to Cathy Cichon for the accompanying graphic, to Solon Kelleher for audio editing, to peer reviewers Dr. Denise Connor and Dr. Andrew Olson.
Zaven: And thank you to Aaron Troy and Dr. Vickie Kassapidis for off-air producing this episode. And thank you to our listeners. We love hearing feedback, as always, so please email us at firstname.lastname@example.org. Opinions expressed are our own and do not represent the opinions of any affiliated institutions.
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Tags: coaching exercises, data gathering, hypothesis generation, problem representation