Welcome back to the master class and again I want to thank the planning committee for the opportunity to be talking about quality improvement and how do we use it to save the kidneys from further damage. These are my disclosures, they have no impact on the content or the presentation that I'll be presenting here today. So when we talk about quality improvement, the majority of the time when people come up and want to talk about it, the question is why? Why should we do this in this particular setting? And I think about it because I'm from the Midwest, why is NASCAR teams so focused on what happens in the pit? They worry about a lot of things, but one of the things that they focus on the most is what happens in the pit. And that's because they understand that what happens in the pit influences the outcome of the race. And so using that analogy, we can apply what happens at the bedside influences our patient outcomes. The work that's been done by the CPR committee internationally and nationally has been incredible. And that's because they now understand it's not just about who's arriving, but it's a matter of what's happening at the bedside. How good are the compressions? Is the depth right? Is the rate right? Does the AED show up? And is there an appropriate charge? And that's because they know that the outcome of that cardiac arrest event isn't completely dependent on the people, as well as being dependent on what happens at the bedside. How well are people functioning in the roles that they need to function in? Because that's what's going to change outcomes. So what do we know about AKI and dialysis in our current setting? We know that it's very complex. We know that this care can be very technical. We know that our patients are dynamic. They change from minute to minute, hour to hour. What applied last hour doesn't apply this hour. But we also know that each and every one of us from institution to institution are doing it a little bit different. And through multiple research studies, practice variation really limits our ability to identify best practices. If we cannot compare our apples to apples, how do we know what's the best thing to do at the bedside? Ultrafiltration is a perfect example of this. We really struggle with how much is too much and how much is too little. Because our patients are dynamic, but we're also doing it very differently. But also, what we don't know. These are great studies that have been published in the last two, probably 15 years, looking at when to start, when to stop. What's the dose? How frequently should we do it? Is a sled-type version better than a continuous-type version? But what there is here is there is a major assumption that the care that's being delivered is the same across all of these multicenter studies. And we don't know that for sure. So if we know that we need to apply quality improvement, what's the resistance? And it always comes down to the same barriers for anything. It's people and money. It's people and money. Oh, yeah, and it's money. Because this costs money to have the right group in place to be able to provide data. Because that's what we need. In order to impact outcome, we need data, which means we need people to be able to look at it. It can be a very circular conversation, right? We need to have data so that we can prove that we need to have an improvement in this, but we need to have data to prove that we need this person. But it still starts with data, because data is what's going to drive change. And Deming said it best. We cannot improve what we don't measure. If we don't know that we are not identifying AKI for two days in our institution, then we can't change that. If we don't know that it takes 12 hours to get a patient on CRRT, then we can't change that. So in order to improve the outcome, we have to be willing to look at our data. Dr. Khashoggi and the AdKey 22 group looked specifically at how do you apply and where is it appropriate to apply quality improvement in this setting, in AKI from community-acquired AKI to hospital-acquired AKI to how do you manage AKI to diagnosis. It's specifically in the follow-up. And so how do we use quality improvement across this continuum? And it starts with standardization. It is very difficult to do quality improvement work in any setting when we have huge practice variation, because if I prescribe a blood priming procedure, because I'm pediatrics, that's different than what my colleague down the hall does. When we have a patient that doesn't do well, how do we determine that it was the procedure versus the patient? We can't. So it starts with standardizing how we deliver the care, and that starts locally. Ultimately, it would be fantastic to start having more standardized across institutions, but we have to start with what we're doing at the bedside in our own institutions, so that we can understand our processes and how that influences our outcomes. What are the right quality indicators for any of these? For AKI, CRT, hemodialysis, peritoneal dialysis, for rhesus. And we just have to sort of look at what is an ideal indicator. Ideal indicators measure efficacy, safety, and outcome. And that's an important piece when we're talking about getting started. There are a multitude of indicators that have been published, but when we're getting started, we really want to focus on indicators that measure all three of these, because these are the most effective. So where do we start? We start small. We start what's easy to collect and has the greatest impact. And that can change from institution to institution. If a delayed start is really a big challenge in your institution, then that might be where you start, because that's easy. When was the order placed? When did the bag show up? When did things get primed, and when did the patient go on? That's pretty simple data collection to really identify a process. And it could potentially have the greatest impact, right? If you can save nursing time and have more time on, you can influence patient outcomes. Specifically looking at AKI, this is some work that was published in 2017. Specifically looking at the implementation of an AKI algorithm. And by implementing this, they were able to look at the processes all along this care pathway. And each and every yellow circle here is a quality indicator. Could be a full quality project. Because how each of these squares get, how one square gets to the next square is about the process. It's about figuring out how do we move that along and how do we impact patients. When they looked at the implementation of this quality improvement algorithm, the AKI, incidence of AKI went down. The length of stay associated with AKI went down. Days to recover AKI went down. And hospital acquired AKI went down. So by informing, understanding, intervening, they were improving overall AKI at their institution. Specific to renal replacement therapies, what are good quality improvement measures? This was a publication by Dr. Waywa and colleagues in 2017 that sort of highlighted themes. And then potential measures. And again, looking at where's the easiest to collect and the greatest impact. And what these articles all have in common is they measure filter life. They measure dose. So those can be easily collected. And then you can benchmark. So many studies report quality indicators without having it highlighted as a quality indicator. And that's an important place to start. So we talked about doses out in almost every article about renal replacement therapy that's specifically start, stop, outcomes based. This was a fantastic quality improvement project that was done by Griffin and colleagues that specifically looked at the dose received for their patients. So between 2016 and 2017, they had 837 treatments. Their interventions were standardizing their protocol because they understood that they were all doing it very different. Standardizing their documentation. And using their EMR to help them calculate the delivered dose. When we make it easy to do the right thing, people will always do the right thing. And what they found was through this robust quality improvement, and then of course interventions, was that the average daily dose improved from 33% to 66% of the time they were in the target dose. So it's not so much about what is the target dose. This group said it's 20 to 25. And they wanted to see the impact of getting it to 66%. The other thing that was significantly different was their week to week dose variation. So these patients were now consistently getting a standardized dose. Downtime. Downtime is a fantastic quality indicator in renal replacement therapy. And this was an article that was published by a group of nurses that specifically looked at recognizing that they had a significant delay in restarts. Through interventions and redesigning their care model, how they delivered care, they were able to improve their delay, actually, decrease their delay in care. And by doing this, one of the things that they looked at, because they were specifically looking at their care delivery model, they didn't have any adverse events. So as they shifted responsibilities from group to group, there was no adverse events or increase in disposals. And that would make sense as increasing your disposable use would imply that you're struggling to get therapies done. This is work that was done by Dr. Nairie and his group out of the University of Kentucky, specifically looking at a very unique quality indicator. Fantastic idea. The number of access alarms. So using the data that they generated from their machine, they were able to look at the number of access alarms, help people understand how to navigate access alarms. And through that work, they went from almost three averaged access alarms down to almost one and a half. So almost a 50% reduction just by looking at one indicator. And even more importantly, when they looked at this, because they are now navigating access alarms better, they had a reduction in cost. So the number of filters that went down decreased. And that was a reduction in cost. So they now can prove that through a quality improvement project, we can reduce the cost of delivering this therapy. This was an article that was published by Mayer and colleagues in 2020, specifically looking at mobility. We are all talking about mobility. And how do we mobilize these patients? And how do we use quality improvement to navigate setting these up? This was really a study that just looked at what are the barriers? What are the challenges? Because that's where it starts. But they did conclude that we can do this safely with the right things in place. And this is work that Molly Vega did looking at nutritional markers on renal replacement therapy. That showed through quality improvement, you can improve the delivery of nutrition. Just by measuring it. By knowing what you have, targeting, intervening, and remeasuring. So when we look at these last three quality improvement projects, I sort of want you to think about what do they all have in common? The first one, really high number of access alarms. The second one, very few patients are actually getting physical therapy on renal replacement therapy. And then the third one, 22% of patients initially were not meeting their goals. Not meeting their nutritional goals. Sorry. What these all have in common is that all of these groups were willing to be vulnerable and look at their own data. And publish it. And publish it. It's hard to think about not delivering the care that you think you're delivering. Each and every one of these was willing to look at their data and say, we can do this better. So unapologetically, we can improve. And then publishing. But data, it's about improving change. It's about moving the needle. You can put it in a beautiful dashboard. You can put it out there for the world to see. But you need to use the data to drive change. It's only as good, data is only as good as what you do with it. So use it to move the needle. Because that's how we're going to change outcomes for our patients. So just a few takeaways. If you're new to quality improvement, start small. Start with those big impact, easy to collect, that sort of cover a wide variety of processes. Generate that data and analyze it. Even if it's one marker. Look at your filter light. Look at your downtime. One marker. Because that will lead to the next marker. That will lead to the next marker. And the next intervention. And it's all about collaborating. No quality improvement can be done in a silo. And reach out to those who have been doing it a while. They can help you get started. And with that, I will thank you again for your attention. And be available for questions at the end.

quality improvement

kidney care

standardize care practices

data collection

renal replacement therapy