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Embedding Equity Into Safety Reporting System

Learning Objectives:
1. Describe an example of how equity is embedded into the features of a safety reporting system
2. Describe how the safety reporting system utilizes integration with electronic health record (EHR) information to collect patient demographic data
0.25 Credit CME

This introductory course introduces the framework for embedding equity into quality and safety, which was developed by Brigham and Women's Hospital and the Institute for Healthcare Improvement. This activity will provide an overview of the five focus areas and how the framework was implemented at Brigham and Women's Hospital.

This video excerpt was taken from the official Kick-Off of the AMA's Advancing Equity through Quality and Safety Peer Network in January of 2022.

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Video Transcript

Karthik Sivashanker, MD: [00:32] We're going to talk about what we did in terms of the reporting solution, because an important part of this is getting folks to actually identify inequities and report it, so that we can then respond to it, track it, do something about it. So I'm really glad to have Andrea Shellman here with us. So Andrea, maybe you can introduce yourself and then talk through some of this, about how we did it.

Andrea Shellman, MHSA, CPPS: [00:59] Sure. Thank you, Karthik. It's great to be here. My name is Andrea Shellman. I'm the Interim Director for infection control, compliance and patient safety at Brigham and Women's Faulkner Hospital, and also a member of Brigham and Women's Hospital department of quality and safety. And this is our… the screenshot that you're seeing here is a screenshot of our safety reporting system. Some of you may be familiar with RL, which is the vendor of this system. And it's what we use if something goes wrong, as it relates to patient care, or if we nearly make an error, but catch it. So for example, if somebody comes and they trip and fall in the waiting room, we would click the appropriate falls icon, and then begin the process of reporting that safety event. We also use this system—it's used by our patient family relations team in order to report patient complaints, compliments that we have those as well, and other concerns. And so the process that I'm describing is similar both for our safety reports that are submitted, as well as for issues related to patient family relations and complaints.

[02:11] So when we first were considering how do we want to report things related to health equity, bias, discrimination, we sort of debated should we have our own icon as in, you know, racism, or health inequity is an event of itself? Or should we embed this into all of the individual icons that already existed? And we decided to go forward with the latter approach. I think that oftentimes, it's not one simple thing, it's not just that our systems discriminate against certain groups of people, it's not just the behaviors that people have, or even their knowledge, skills, and abilities. But those are all embedded within the everyday things that we do and the everyday errors that we have. And so it's for that reason, that we decided to embed this…embed our method for capturing bias and discrimination into each individual type of event. So you can click to the next.

Sivashanker: [03:10] That's a really important point and a decision point that you all are going to have to make, but I… Andrea, my sense is that that has worked out well because it's consistent with this whole idea of this is what we're supposed to be doing anyways. This is part and parcel of the quality and safety work. So rather than making it something separate, like we have tended to do historically—like we're going to do the DE&I thing over here—it's just this is our quality safety work, and as part of that, we're always thinking about equity. And we should be looking for an equities whether it's a fall or a [unintelligible], or CLABSI, it doesn't matter. So I think that's worked out well, overall, but just something to flag and, Andrea, if you have a comment and Anad, I see your hand's raised as well.

Andrea Shellman, MHSA, CPPS 03:53

I would agree with what you've just said. Did you say somebody had their hand right? Oh, yeah, go ahead, Anad.

Anad (participant): [04:00] I was just wondering, because I think sometimes with these reporting things, the person doing the reporting or somebody engaging it has to actually see what's going on with an incident or a situation with respect to either a provider who's, who maybe… There's a lot of basically gaslighting that goes on with respect to patients and providers in terms of people's experience of racism and bias and things. So I'm just sort of curious, because when I've seen, in my past, like when I've seen some of these incidents happen, a lot of times people experience a thing, the patients experience a thing, and many times those feelings are diminished or not taken seriously by people on the other end, and they lead to some of these safety incidents. So I'm curious how you sort of process some of these things because the some of the people involved with these incidents may or likely not seeing any of this stuff at all, as they're going through these particular cases.

Karen Fiumara, PharmD, BCPS, CPPS: [04:48] Anad, the big piece that I took away when we started this is making sure that we're really clear about the difference between intent and impact. And that there just needs to be that distinction there that, you know, the intent… And while sometimes we call it gaslighting or whatever, somebody felt a certain way about something. And I think that part of all of this work is the, like, let's talk about that. Let's normalize that, let's talk about impact and the intent. And hopefully bring teams together around that. Now, I will say that one of the areas that's unbelievably helpful is, you know, at Brigham and Women's Hospital, we have a group called OB cos that really deals with like, interpersonal conflict resolution, and we have amazing leaders in our DE&I space that really help us like, process some of these things.

[05:53] In my mind, you know, got to put it in there. Let people put in what their thoughts are. And then the other piece is that just, sometimes somebody will report so and so did X, Y, and Z thing wrong [background noise] on a different shift, on the shift before me. And then when you do the investigation into that, that was the perception, but the fact set is very different. I had to normalize that here, too. Just because somebody's name was… we have a standardized process, we have a standardized workflow. We'll work through it and at the end, we'll come up with what the fact set is, and hopefully all arrive at greater understanding Does that answer your question? Does that help at all?

Anad (participant): [06:43] Yeah, I think what the impact thing is, I think even… Well, I'll just say that I don't know that… I've been in situations where I'm not sure people, well, see the impact of some of their behavior.

Fiumara: [06:57] Or, that's why it's like, straight up the middle. It's kind of… and I use that—Andrea can tell you—I use that term, probably way more than I should, you know? This is going to feel like we're running the football straight up the middle, and we are. We're going right past-the-nose tackle and… But I think that it is, it's definitely difficult.

Sivashanker: [07:26] And what you're going to find is that--so, Andrea is going to get into how we actually put in the language and all that—but what you're going to find is that first, not everyone's going to report. It's going to be the early adopters that report. It might even be more residents early on or trainees. It depends on who you socialize this with. So there's going to be some work to do once you've embedded this to actually let the system know that this is available, that they should be using it. So that's one part.

[07:55] And then the other part is that how people report will be variable, right? So you might have folks coming in and writing some details that the language isn't…is perceived to be inflammatory, or accusatory, or… and you're going to have to manage that, right? Because on the one hand, you don't want to censor what they say or be overly prescriptive--don't say these types of things, because we don't want to injure the other staff. So these are things you're going to have to figure out as a team, which is: you've gotten a report, And it's one person's perspective. Now you need to do the work of collecting all the other folks' perspectives, and integrating it, and potentially bringing folks together to have a discussion about it, which requires safety, which requires not having a blame kind of stance. And so these are all things you're going to be grappling with. I'm loving that we're going there in the discussion, we're supposed to be focused on just the simple stuff of like, how do you put this in your reporting solution? So let's go back to that. Andrea, can you just describe how did we end up doing it? And this is not meant to be like this is the only way. This is just how we did.

Shellman: [09:08] All right. So this is the demographic section of our safety reporting system. And as you can see, you start out by just sharing if it's an inpatient, outpatient visitor, that sort of thing. The search buttons that you see here, the little magnifying glasses, that actually connects to our medical record, for lack of a better—not directly the medical record—but the ENPI. And so we can search through all of our patients based on their MRN, their first name, their last name. And once that's done, the rest of the things auto-populate, so the date of birth, the person affected race, the ethnicity, and language, all of those things auto-populate based on what's in our medical record.

[09:47] So the good thing is that people aren't guessing these fields. One of the challenges that we have had is around capturing that data, which is a whole ‘nother conversation, but we are able to align what's with what's in the medical record. One of the challenges, that said, is that using this search function is not a forced thing, so sometimes people use it and sometimes we'll just freehand things. But that's sort of one of the challenges that we are kind of working with. So that first part that I mentioned, captures the race, ethnicity, language data. The second question that you see there towards the bottom: "Is there a concern for bias or discrimination in this case?" This is an optional question. It's basically a yes or no; yes, or no/unsure. And if somebody clicks yes here, then we ask them the second question, which says, "Please provide additional details regarding your concern for bias or discrimination." This is actually a more recent development, something that we added after probably a year or so, just finding that oftentimes, we will add select yes and as we'd read up the report on the surface, it seemed like "Why, you know, what's the concern? This is a 50-year-old male from a rich suburb and like, how are they concerned about discrimination?" And just—Karen, so I, this may be a little sensitive topic—but one thing that may come up, it could be, I'm concerned that this patient was discriminated against, because they elected not to take the COVID vaccine. So that is something like that's an example that we have seen. So if we hadn't have asked that question, then we may have sort of dismissed this as like, oh, maybe this picked the wrong thing, I don't get it. Or it may have taken a lot more effort in order to uncover what their concern was around discrimination or bias. So it's been interesting to see that sometimes it's related to race, ethnicity, language, ability. And sometimes it's things that we, that wouldn't necessarily be on the forefront of our mind.

[11:42] Next slide here. Some of these things, I think, on the next slide I've sort of already gone over. And I think probably, I won't do a demonstration just for the interest of time. But these are some of the things that we are capturing: race, ethnicity, and language. I think the things that you see on there, on the right, are really opportunities for us. Sexual orientation and gender identity. We do capture gender, which is more of the gender that you are assigned at birth, as opposed to somebody's own gender identity, but that's an opportunity for us, and we do capture age as well. So yeah. [pause] And in terms of capturing reporter demographic data, that's something that we're not currently capturing right now. If we were to capture that currently, we would probably have to ask somebody, ask the reporter to answer these questions. And we've had challenges in sort of integrating our HR systems with RL and being able to automatically capture this information, but I definitely think it's an opportunity that we'll probably see some discrepancies in terms of who's reporting in various groups. So just something for us to consider both the person that was affected as well as the people that are reporting.

Video Information

Credit Designation Statement: The American Medical Association designates this enduring material activity for a maximum of 0.25 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

CME Disclosure Statement: Unless noted, all individuals in control of content reported no relevant financial relationships.

If applicable, all relevant financial relationships have been mitigated.

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