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SCCM Pod-483 Clinicians, Patient Outcomes, and Implicit Bias

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6/29/2023

​Implicit bias is a form of automatic and unintentional bias that affects judgments, decisions, and behaviors. Implicit bias can pose a barrier to the diagnosis and treatment of critical illness. Ludwig H. Lin, MD, is joined by Varun U. Shetty, MD, to discuss ways that critical care professionals can mitigate diagnostic delays and errors by being aware of their own implicit biases. Dr. Shetty is an adult intensivist who focuses on caring for critically ill patients in global health settings. He has worked both in the United States and abroad in resource-limited settings and has presented several lectures on healthcare disparities with a specific focus on the care of critically ill patients. This podcast is funded by the Gordon and Betty Moore Foundation through a grant program administered by the Council of Medical Specialties. 0.25 hours of accredited continuing education credit is available for this podcast through June 30, 2024. Visit sccm.org/store for details.

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Category: CCM Podcast

Transcript:

Sponsor: This podcast is funded by the Gordon and Betty Moore Foundation through a grant program administered by the Council of Medical Specialty Societies.

Dr. Lin: Welcome to the Society of Critical Care Medicine Podcast. I’m your host, Dr. Ludwig Lin. Today, I’m joined by Dr. Varun Shetty, MD, to discuss implicit bias in healthcare. Dr. Shetty is an adult intensivist, soon starting at the Cleveland Clinic Foundation. He focuses on caring for the critically ill in global health settings. He has worked with physicians in the United States and abroad in resource-limited settings. He has also given several lectures in healthcare disparities with a specific focus on the care of the critically Ill. Welcome, Dr. Shetty. Thank you so much for taking the time to talk with us. This is such a great topic and one that we can all learn about. Before we start, do you have any disclosures to report?

Dr. Shetty: Hi, Dr. Lin. I do not have any disclosures but I do have my own biases.

Dr. Lin: Well, that’s a good setup for this conversation. Yes, let’s start and let’s talk about implicit bias, if you could define for us what implicit bias is, and how does it develop?

Dr. Shetty: Sure. The first thing to remember is that everybody has implicit bias. This is a human trait. It is an evolutionary trait. If we wanted to put a definition to it, we can call it an automatic nondeliberate attitude or belief or idea or prejudice that people hold unconsciously. This is different from explicit biases such as sexism and racism, and it can often be at odds with one’s own belief systems. For example, I consider myself a feminist but when I took the Harvard Implicit Association Test, which we will talk about in more detail a little bit later, I found out that I had a moderate bias against working women. I was embarrassed and surprised but also I thought it was a great learning opportunity for me to be aware of my own biases. So I’m paying more attention to it going forward as I go about my own life. That’s implicit bias in a nutshell.

Dr. Lin: That’s a really good explanation. Thank you so much. I was just thinking to myself, that is pretty incredible that you took this test, this tool, and realized that you had implicit biases because I’m assuming that you’ve thought about all of this a lot and you’ve worked really hard to try to be as bias-free as possible. Tell me more about that. Were you surprised? Were you shocked? Or did you think, “Well, actually that’s how this works”?

Dr. Shetty: Yeah. It just goes to prove that none of us are bias-free. We all have our biases, and the trick is to figure out where our individual biases lie. Once we know our biases, and this by no means is perfect, we will not master our biases, but we can mitigate the effects from those biases if we are aware of them and we start working toward them. This is the process, and it’s ongoing.

Dr. Lin: That’s a really nice way to think about it. We are all on a self-improvement journey, hopefully. That’s good. Just as a follow-up, how does the presence of implicit bias impact or, let’s just face it, how does that harm the various elements of the healthcare environment?

Dr. Shetty: That’s such a great question, such an important question. We’re going to talk about some of the studies around implicit bias and how it affects patient outcomes later in the talk. But I want to talk a little bit about one of the theories used to explain implicit bias, which is the dual process theory of thinking, where it splits human cognition or human thinking into two types, type 1 and type 2. Type 1 is the more instinctive, the intuitive part of it, it’s super-quick. Most of our decision-making happens in the type 1 realm, and it is especially so in stressful situations, in situations when we are tired, when we are sleep-deprived.

The slower, more deliberate, more analytical thinking is the type 2 processing. Implicit bias is often a result of type 1 thinking. Actually, one of the ways to mitigate it is to slow down our thinking and switch over to the analytical side of it. Since we all have biases and since we are all in these high-stress situations, these biases that are out of our control often develop into actions and then, downstream, result in poorer patient outcomes.

Dr. Lin: Can you give some examples of situations where implicit bias in, let’s say, a physician winds up affecting the way care for a particular patient or their family plays out?

Dr. Shetty: That’s a great question. For example, I was once rounding in the ICU and I had a patient who was post-cardiac arrest. I was told by the nurses and by several people that the family was difficult, and this was an African-American family. When I met the husband of the lady who was my patient and the two children, they couldn’t have been friendlier. They couldn’t have been nicer. They were very passionate about his wife, their mother. They loved her dearly and we had some of the most connected conversations. My experience with this family was nothing close to the descriptions provided by the ICU staff. I wondered what the reason was for this and I will never have a correct answer, but it leads me to wonder how much of this was implicit bias, how much of this was intuition, and how much of this was just bias playing into how we perceive other people. That’s just one of the examples of how bias could play a role, and that’s anecdotal.

Then, if we want to talk about other studies, there was a retrospective cohort study that looked at interhospital transfers in patients with sepsis; they looked at the control for various comorbidities. They found out that Black people and women were far less likely to be referred for transfers from a lower-level hospital to a higher-care hospital than other people. Similarly, a disparity trial looked at the time to antibiotics in people and found that women had a median of a 31-minute delay in getting antibiotics, and fewer women got antibiotics within three hours.

Dr. Lin: Wow. That’s a big deal. That goes against all of our sepsis initiatives.

Dr. Shetty: Absolutely. It’s hard for physicians, me included, to grasp my mind around something as subjective, something as intangible, as implicit bias. But it’s real, it exists, and we see real-life consequences of it.

Dr. Lin: Yes. This actually makes me think about another major public health topic that’s been in the general conversation recently, which is poor maternal health outcomes, especially in African-American women. I have no doubt that part of it is the result of implicit bias. It’s just like any other type of medical error. It’s a Swiss cheese thing. There’s never this one thing, right? It’s a whole series of things and implicit bias might be one of them, but it could potentially lead to very poor outcomes. Do you agree?

Dr. Shetty: That is absolutely correct. In fact, Serena Williams herself, her symptoms were ignored during her pregnancy until they discovered that she had a DVT and a PE. There was actually one study that looked at Hispanics versus non-Hispanics in the ED, and the Hispanics were far less likely to get prescribed pain medications in the emergency department. A study in children revealed that Black children were less likely to receive adequate opioid pain medications than non-Black children. This is real, and what you are talking about is also real. I wouldn’t be surprised if implicit bias is leading to these outcomes.

Dr. Lin: We could link this to so many things. Another ICU topic, technological bias in terms of, for example, pulse oximetry. During the COVID pandemic, we talked about how it turns out that pulse oximetry is not designed for people with darker skin. Again, not one single thing, but all of these things combined, and what happens? Poor outcomes, right?

Dr. Shetty: That’s exactly right, because where do these systemic and institutional biases originate? They originate in the individual, and because it’s unconscious and unrecognized, individuals who are well meaning can lead to these poorer outcomes.

Dr. Lin: When experts like you are thinking about implicit bias, which subgroups is it happening to? Are we talking about skin color? Are we talking about socioeconomic status? What are the different conditions that predispose to implicit bias?

Dr. Shetty: Another great question, Dr. Lin. I suspect that our data are only capturing a small part of what’s going on in larger society. I must also add that the studies that we are discussing here and the context that we’re in is a Western context and, more importantly, a North American context. A lot of the studies that we are seeing here are coming out of the cultural milieu of North America, which is they’re focused on Black versus non-Black or men versus women. We’ve seen consistently that people of color and women are being treated worse than White men.

Dr. Lin: Okay. What about things like age?

Dr. Shetty: There was at least one study, the sepsis study that I talked about, where we were looking at interhospital transfers. Older age was also one of the factors that led to fewer transfers. Older people were not transferred as much compared to their younger cohort.

Dr. Lin: What about things like the presence of somebody who’s less able-bodied?

Dr. Shetty: I have not come across any studies for disabled individuals. But I’m thinking that if we start focusing on those individuals, not just less able-bodied individuals, but also transgender people or people who are on the gender-queer spectrum, it would be interesting to see what kind of biases and what kind of outcomes we see in studies.

Dr. Lin: Agree. I would be really curious about that. I would like to think that all of us are actually very well meaning. We want the best. But you don’t know what you don’t know. You don’t know what you are not even seeing, right?

Dr. Shetty: Absolutely.

Dr. Lin: This is such a huge topic. Now that we’ve talked a little bit about implicit bias, who it happens to and the types of harm that it could produce, I’d like to talk about the potential actions that we can all take to reduce it. Maybe you could tell us more about that.

Dr. Shetty: Absolutely. I think the first step toward mitigating implicit bias in our clinical settings is to know ourselves. One of the easiest and most accessible tests is the Harvard Implicit Association Test. If you Google it or search on DuckDuckGo, you’ll find it and it’s available for free. What this test does is it looks at associations in your mind but also looks at speed of associations. For example, it’ll give you a certain key for White individuals if you’re looking at White and Black dichotomies. For White individuals, you’ll have certain words like glorious or joyful or wondrous. And for Blacks, you might have scary, angry, fearful.

Then they’ll ask you to switch it and they will test how fast you react and how fast you associate these words with which race. That takes out some conscious thinking and brings us down to these subconscious associations that we make. There are various kinds of implicit bias tests that are there on that website that you can take. You can go crazy and look at various associations, but I think that’s a really good start to knowing your own biases.

Secondly, being aware that in stressful situations, in situations where we have lack of sleep, know that you will lean on type 1 thinking. It’s not always a bad thing. It’s how we survive. We survive because we are able to make fast, intuitive decisions. That’s good when we have a patient who’s tachycardic and hypotensive and we’re thinking about starting to give them fluids, doing an ultrasound, getting blood cultures, throwing in antibiotics. But it’s bad when we are not quickly treating a Black person with pain. So knowing ourselves helps us use our thinking to our advantage and to other people’s advantage.

Thirdly, knowing the individual, just knowing your patient at a personal level, what makes them happy, what is a good quality of life for you, will help you overcome some of those biases. At a system level, checklists. Atul Gawande has written about this, and we know checklists are so useful. They also help mitigate bias in the hospital.

The other thing that I think more and more hospitals should adopt is implicit bias rounds. Just like mortality and morbidity rounds, we should consider discussing a case a month or every couple of months where we focus on how implicit bias affected a particular patient outcome and really do this in a blameless fashion where we are trying not to point fingers, we are not trying to single out people and call them bad people or call them racists, but talk about this as a human problem and keep this topic of implicit bias on the surface of our consciousness and really think about implicit bias when making policy. If you know and agree that we are all prone to implicit bias, we will be more careful when we make policies at any level.

Some of the other ways to mitigate bias would be counterstereotypes, where we think about the opposite of what a stereotype might be, and these stereotypes might be different for different people, and thinking about slowing down, switching from type 1 thinking to type 2 thinking where we are switching from intuitive thinking to more deliberate analytical processing. These are some of the ways in which we can mitigate bias.

Dr. Lin: That sounds really good. You talked about checklists. We love checklists because they really, like you said, make us take a little pause, be more intentional. Is there a checklist for implicit bias that we could all use?

Dr. Shetty: I don’t think there can be a catch-all checklist, right? I think what we have to do is keep looking at the literature. Just like we do with everything else in medicine, see what’s coming out in the literature. And what’s coming out in the literature is that we are not treating patients’ pain well enough. We are not giving women antibiotics soon enough. Our nonverbal communications are not the best. I think focusing on those things, on individual problems as we go, as part of an ongoing QI process, would be useful without really increasing the burden of documentation. I think this would be different for different institutions. For different problems, there would be different solutions, but it’s one of the solutions that we can have to mitigate bias.

Dr. Lin: Got it. I wanted to follow up on the proposal you had, which sounds wonderful, about having implicit bias rounds. That makes me think though, what is the group that would, for example, adjudicate about whether implicit bias had happened? Is there a gold standard? Or do you almost need a subgroup of people to look at each particular situation? Because it would be hard for any one group to be totally bias-free, for example.

Dr. Shetty: Absolutely. I think the way we could approach this is just the way we approach mortality and morbidity, we rely on residents and physicians and nurses to send us cases where they think that implicit bias might have occurred and in what way. There could be a committee of people who decide which case to take on and what to discuss because, remember, this is not about judgment. This is not about diagnosing. This is about using a case as an opportunity to discuss what bias may have occurred so it remains at the surface of our consciousness.

Dr. Lin: It’s a lot of learning and it’s going to take a lot of humility, isn’t it? I wanted to change focus a little bit and ask you, how did you personally get interested in this topic?

Dr. Shetty: It’s difficult to pinpoint exactly when I started but one of the most vivid memories I have is listening to the story about the killing of Michael Brown and then the several other shootings of Black individuals that followed, that were always happening and that we just started talking about got me thinking about bias. Then I started examining the role of race in medicine and how casually we used race as a surrogate for genetics in medicine and how there were so many problems with that. In fact, I went on to do a talk about race in medicine, and that was my senior talk for graduation during residency. Then finally, during fellowship in Pittsburgh, Ann Thompson, who I had the great pleasure of doing this webcast with, gave a fantastic talk on implicit bias that stayed with me. That’s how I came to this, and the rest is history really.

Dr. Lin: That is very cool. I just really like how that also manages to speak about allyship and sponsorship. Good for you and definitely good for Dr. Thompson. That does remind me that one of the incentives for doing this podcast is that you and Dr. Thompson are doing an SCCM webcast about this topic, which is great. I’m hoping that it will live on on the internet and people can check that out. How would you respond to those people in the critical care world, or even just in the medical education world, who hear of you speaking on this topic and say that it’s virtue signaling, that it’s not actually useful?

Dr. Shetty: I think that’s the elephant in the room, right? I think we need to address that. It’s important for us to remember that we are not blaming any particular set of people. We are saying that this is a human trait. Everybody has implicit bias and it has gone unrecognized for too long, and too many patients have suffered for us to not take notice. If this were a medical intervention or this were a drug with so many sources of evidence, we would be talking about it a lot more. I’m glad we’re talking about it now, but there would not be a question whether it’s important. It’s really not about saying, I’m better than you. No, we are all in the same boat. We all have implicit bias, and we all collectively have to figure out how we can do right by our patients.

Dr. Lin: I love that way of framing this. It’s so true that implicit bias occurs in a lot of different places within medicine. Even as you were talking about it just now, stressing the need to cast aside who’s right, biases occur everywhere. And look, one of the biggest advances that happened when I was training, for example, was the realization that you cannot rely on the bedside physician’s gauge of whether somebody’s ready to be extubated, for example, for respiratory failure, that establishing daily protocols and checklists and making it objective actually removed a lot of the medical implicit biases there. So this is kind of everywhere, you know?

Dr. Shetty: Absolutely. I mean, this is a human form of thinking. There’s no escaping it, but we can mitigate some of its downsides.

Dr. Lin: I wanted to ask you about what you’ve seen in your time in the critical care world in terms of implicit bias. Have you seen any changes? Have you seen any trends since people like Dr. Thompson started talking to you about this?

Dr. Shetty: I think people are definitely more receptive. We are talking about this a lot more. I think people are willing to listen. I think journals are giving space to more and more articles around implicit bias. Organizations like SCCM and us doing this podcast and the webcast are all evidence that we as a community are recognizing the importance of this. I think it’s a positive trend. I think we’re going in the right direction.

Dr. Lin: Let’s talk about how to help our community get better at this. We all love data. What types of literature are out there to talk about the impact of implicit bias on patient outcomes?

Dr. Shetty: If there’s one paper that you want to read about implicit bias, I would recommend the paper by Elizabeth Chapman and colleagues in the Journal of General Internal Medicine. It’s called “Physicians and Implicit Bias: How Doctors May Unwittingly Perpetuate Health Care Disparities.” The other paper, if you want to do a little more deep dive, is “Cognitive Debiasing.” It’s a two-part paper by Croskerry et al. There’s also a great book on implicit bias called Blind Spot, which was written by authors who brought about this term and popularized the term “implicit bias.” There are a lot of resources out there. There are a lot of great review articles, a couple of which I’ve mentioned. SCCM is also going to have a companion document, which has some more resources listed. Stay tuned for that.

Dr. Lin: Perfect. Thank you so much for mentioning those papers and thank you for telling us about this accompanying document. Where is that going to be found?

Dr. Shetty: It’s going to be part of the webcast resources, so you should be able to download it. I’m not exactly sure where, but I think it’s somehow associated with our webcasts.

Dr. Lin: Got it. I think we all know about Dr. Wes Ely’s delirium website. Are there websites about implicit bias that people can go to for more information and for self-education?

Dr. Shetty: I think Harvard’s Implicit Association Test is a great place to begin. Then, these review articles that I mentioned would be a great way in to this topic and finding more resources. Several teaching universities have their own collection of papers and their own little summaries of implicit bias and how it plays a role. These resources are plentiful and they’re readily available.

Dr. Lin: Sounds great. Thank you. I wanted to make sure that I asked you whether you had any takeaway points or other topics within implicit bias that we should make sure that our listeners take from this conversation.

Dr. Shetty: Absolutely. I think it’s important for us to remember that everybody has implicit bias, that in the ICU, when we are really stressed out, we will lean on type 1 thinking, intuitive thinking, a lot more. We will be more prone to making mistakes based on our biases so it’s important to know what our biases are. It’s important to keep thinking about how we can mitigate it. We will not be able to get rid of it, but there are many ways to mitigate bias. We should all be working in our institutions at an individual level and at an institutional level to mitigate bias because it has real-world implications on patient outcomes.

Dr. Lin: That is such a nice summary of what we’ve been talking about. I appreciate that so much. Thank you again, Dr. Shetty, for taking the time to have this conversation. It’s important. Even just during this conversation, I’ve thought about a couple of medical decision-making and technology items that involve implicit bias. I think it’s important for all of us to come into this with humility and know that this is something that happens to all of us and, only by being very, very intentional and by being aware can we tackle it.

Dr. Shetty: Thank you for having me, Dr. Lin. This has been an absolute pleasure talking to you.

Dr. Lin: Oh, good. Well, on that front, this is going to conclude another episode of the Society of Critical Care Medicine’s Podcast series. If you’re listening on your favorite podcast app and you like what you heard, consider rating us and leaving a review. For the Society of Critical Care Medicine, I am Dr. Ludwig Lin.

Sponsor: This podcast is funded by the Gordon and Betty Moore Foundation through a grant program administered by the Council of Medical Specialty Societies.

Ludwig H. Lin, MD, is an intensivist and anesthesiologist at Sutter Hospitals in Northern California, and is a consulting professor at Stanford University School of Medicine, where he teaches a seminar on the psychosocial and economic ramifications of critical illness.

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Some episodes of the SCCM Podcast include a transcript of the episode’s audio. Although the transcription is largely accurate, in some cases it is incomplete or inaccurate due to inaudible passages or transcription errors and should not be treated as an authoritative record.

 

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