Karthik Sivashanker, MD: How do we want to begin this work? And there's many different places to begin, I think that's one of the challenging things when we're talking about doing equity work is, you know, where do we start? Do we start in a particular initiative? Do we start with employees? Do we start with patients? So we're offering a very specific approach here that we have found to be very powerful. And that begins with our harm events, our risk event, so integrating equity into all of our quality safety risk analyses. And we'll talk about what that means using equity-informed quality safety education, using data to support equity improvement, engaging leaders, and building awareness, and then organizational accountability. So let's go to the next slide.
And we'll talk a little bit about what that means. So it starts simply. And the first question is just going to be: Are there inequities contributing to this risk? This is something you can start to do today, tomorrow, with every single risk, whether it's a safety event that's been filed, if it's a patient complaint, if it's an HR complaint. You can ask this question, are there any inequities contributing to this risk? And if so, at what level? So let's go to the next bullet, which is: Is it interpersonal, or implicit? Is it institutional? Is it structural? And getting in a habit of thinking about it at all those levels. Now, what I'll say is that as you start to do this, there's going to be a lot of potential contributing factors at each of those levels, and you can easily start to feel paralyzed, like, how am I possibly going to address all of these institutional or structural factors? But it's important to begin by just asking the question and thinking about it and identifying it. And you'll start to see why that becomes really important.
So we start with the question, next slide. And then we want to do this in an identity conscious way, not in an identity blind way. So what do we mean by that? So usually, when we do our safety risk event analyses, we do it like this: Say a 60-year-old woman has trouble getting her medication at the pharmacy. We've taken identity out or demographics out because we think we're being more fair that way. And there is a reasonable rationale there, which is, when I provide demographics, we all have implicit biases, we're prone to just have those implicit biases be triggered and to act on them. Right? So it's, it's really critical that we are careful around this. It's important to prime folks to say there's a reason we're bringing this in—it's so that we can systematically identify and address inequities as the integral part of the work that we do.
So what if the real story is this next version, which is a 60-year-old, non-English speaking woman from the Dominican Republic with low vision has trouble getting her medication at the pharmacy. We've been doing our event analyses the first way, and as a result, we've been systematically blinding ourselves to what is actually going on. We can't actually get the right contributing factors. And so when we start doing these simple things, if you go to the next slide, what you're going to find, most likely, is that you're going to go from missing inequities as the rule to starting to identify a whole lot of inequities. And this is what we saw at the Brigham and Women's when we started doing this work. Just this simple thing is going to start with, helping with identification. identification is the first step.
And really, this is what progress looks like. It's more, not less, reporting of inequities. It's more complexity, and more discomfort. No one ever said this work is easy. And no one ever said this is going to be wrapped up with a nice bow at the end of it. These are going to be messy cases. These are going to be cases that involve ethics and justice and things that we don't grapple with all the time on a daily basis, but you're going to be grappling with it. And we need to be comfortable with that complexity, with the discomfort, with not always knowing the answer. We need to be comfortable with liability, because there's going to be a fear if we're digging into this, we're identifying these problems now, we have to do something about it. And if we want to be transparent, well then does that expose us to some sort of risk? But I think… I'm a firm believer—I don't have data to say this, but I'm a firm believer that our risk in terms of liability is not coming from identifying the inequities and trying our very best to do something about it and being transparent, that we've identified inequities and aren't doing something about it. Our risk comes from what we've been doing, which is pushing it under the rug. That's where the lawsuits are going to come from. That's where the risk is going to come from. And more importantly, is what the harm is going to come in terms of our patients and our communities.
Driver two—so how do we build this into our education? How do we build this into our quality safety, education, our DE&I education? A good place to start is with your quality safety teams, your patient family relations teams, the folks that are in this room, our community population health teams. It's just starting to build this equity informed high reliability approach into it. And if you can go to the next bullet.
The reason this is really powerful, and the reason we want to start with patient harm events, is because I can give you all the data in the world about inequities. Most of the folks here have seen data on this, right? We know that pretty much across any outcome, there are inequities, which means differences in outcomes that are preventable, that are widespread or pervasive, and that are unjust. So pretty much across any outcome you look at, there's going to be some inequities. And you've seen the data, but that data doesn't move people—it doesn't shift behavior, right? What does shift behavior is stories. So if I tell you the story of one patient who has been harmed and I give you the details about that harm, and we dig deep into that and we understand all the root contributing factors, and then we layer on data, suddenly we're saying this is something that happened to a real person, a real staff member, a real patient who was harmed. And now we have data to say that it's not just this one person being impacted, it's a wider spread problem. That is something that can compel a board or a leader in an organization to do something. So it's this combination of anchoring the stories, anchoring the work, the education, the quality safety improvement, work around those individual harm events, and then layering on the data that is that is really powerful.
We're also going to talk about, how do you effectively engage leaders? And we're, we have in our faculty, some leaders like Andrew Resnick our, up until very recently, chief quality officer at the Brigham and Women's Hospital, who has now transitioned to his new position, and Karen Fiumara executive patient safety director. So I was lucky in that I had some leaders on board who were supportive and just great allies. But you're, you may or may not have that. So how do you actually move folks? How do you move leaders? How do you move boards? We're going to talk about connecting the work to that.
The long story short is, you know, we've spent 30, 40 years building a safety infrastructure that I think is fairly robust. I mean, not saying it's perfect, we have a lot of work to do to get from being reactive to proactive and even to get more transparent, but compared to where we were, we've made a lot of progress. But when it comes to equity, we're still four years ago, we're basically in the same place the patient safety journey was at in terms of not really talking about these events, and only reacting when something really bad has happened. And you know, being uncomfortable with having these conversations. So we need to socialize the work, we need to get proactive, and this approach is going to help do that. And there's going to be a lot of hard to measure, but important ripple effects from doing it in your culture and in your organization, as you'll see over time.
So I'm not going to go over all of this. I think the fact that you're all here means you're at least interested enough to want to try this out, to learn more, to see what this is going to be about. So I'm not going to go over every single example or way that I think this work has been important. You're going to find that there's lots of ways that this work is going to be impactful in terms of identifying different inequities. There are some examples right there, leading to quality improvement initiatives that are actually helping patients and communities. It's going to lead to updating your data approaches. It might lead to new collaborations. With COVID-19 It's been a really powerful approach just in terms of having an early detection system for an equities. We were very quick to identify that COVID-19 and the surge was differentially impacting our patients because we had this approach; it was like an early detection system.
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