Hi, my name is Mayor Friedman, I'm an electrophysiologist at Hartford HealthCare in Connecticut, and thank you for the opportunity to present our quality improvement process, which was a response to NCDR device registry data. I plan on walking you through our process by which we identified the root cause of our metric outlier, and then how we applied our corrective measures so that we can close that gap. We looked at the proportion of patients who underwent an ICD or a CRT defibrillator implant and who have a depressed left ventricular ejection fraction less than 40% who were prescribed an yeast inhibitor or an ARV at discharge as eligible. The way the database is collected, there are four options which are registered. Choice one is patient received the medication. Choice two, patient did not receive medication due to medical reasons. Choice three is patient did not receive medications due to patient request. And choice four is no medication prescribed at discharge, but no reason given. We measured at 76.6% compliance with that measured metric, whereas the median across the nation was 92%. We chose that metric so we can improve it, as it was one of the few outliers in our database. The EP device implant registry has been the national standard for guideline-based therapy, selection, care, and outcomes in those receiving an ICD. The registry provides us actionable real-time data which empower us in decision-making to provide patients with nationally benchmarked data on care and outcomes. Our institution benchmarked in the metric I outlined prior well below the median. Our intent was to identify the reasons for this gap and formulate and implement a solution to close it. I'm going to segue into our methods to discuss how we looked at this and how we tried to solve this problem. It is a method called lean methodology, and it stems from, I think initially rolled out by Toyota, the car-making company, whereby they tried to streamline production and eliminate inefficiencies, streamline the robotics, the mechanisms, the methods, and the interactions between people, and hence the term lean, to eliminate inefficiencies. We use this in our institution routinely. I've used it for other projects that we used, and I'm going to discuss this for a few minutes. It's called an A3 process, and it's a structured problem-solving tool which fosters learning, understanding the problem, rolling out the solution, re-studying the outcomes, and fine-tuning it further. This includes collaboration between all the stakeholders that are inherently related to any processes. I think it encourages in-depth problem-solving rather than solving each problem as it surfaces, doing it again and again and again. I think this alludes to the lean methodology where you want to eliminate waste. If a certain problem arises multiple times, and there's a systemic root cause, by eliminating the underlying issue, you will solve the problem moving forward automatically on a larger scale without the need to implement solutions again and again. That's exactly what we did for our study. This is an A3 project, and the name actually comes from ... They took legal paper which is termed A3, and they took it and they created four quadrants that you see over here that discuss what's going on now, current state, and then identifies the problem. Then you try to figure out the root cause so that you can solve it, and then you roll it out, your countermeasures, but then you reassess and re-study in the future state to ensure that what you have created is functioning well. This slide underpins that once you have a problem or something you'd like to improve and eliminate inefficiencies, you develop a plan, but the key is not to just plan it, do it, but you have to study and adjust the outcomes because a lot of times major systemic root cause problems are not necessarily easily fixed, and the key is that this is a dynamic process where you're using data to know your current state, implementing solutions, and then following up with updated data to ensure that things are moving in the direction that you would like. This slide gives us a lot more information about the process. We have an opportunity statement. Is this opportunity? Focus is a worthy effort. Why are we doing this? Is there a reason, and if we go through this process, what will we achieve? Then we look at the current state. What is the process? If you want to implement something without actually going and seeing how it's currently done, you may not be able to pick out ways to improve it, so what are we currently doing? What has led us to the current situation? In our particular case, we were scoring 76% on a very important metric. That's what was happening at our institution. Why is that a problem? What is that a problem for? Be as specific and write it down so that you know more targeted approach. How are these problems impacting the patient in our particular case or customers or staff or any process that you want to assess and improve? What is the evidence that we have to support that this is a problem? The next bottom left step is the root cause, and to get to the root cause, experts say you have to ask why five times, kind of like a kid, why, why, why? We were scoring 76%, why? Because we're choosing option four, which is 24% of the time. Why were we doing that? Because it wasn't specified in the health record. Why are we doing that? Are we not following guideline therapy? Are we not aware? Are we missing opportunities? You want to delve into the depth of the problem so you can get to the true root cause because that's the only way to fix it. And then you move to the countermeasures on the bottom right. What's captured there is what are the steps, actionable steps, that we take to fix what we identified as the root cause? And you need champions for each actionable item. You want to take responsibility and have quote skin in the game to make this happen, especially at a big institution or corporation. Imagine Toyota rolling out an improvement. Hundreds of thousands of employees across the system. You want to really focus and improve things. And you want to have a deadline. You want to give it time to implement, but you also want to get back to it and assess what you're doing. And then in the top right, you have something called future state. What are we interested in achieving? What is our target state? In our particular case, we wanted to improve that measure metric to at least a median, which was 92%. What will the new process look like? And will it get us to the solution and target an outcome that we're interested in? How will we know when it's fixed? Data. Data is very important. And once we fix it, is it sustainable? How can we sustain it? How can we improve it further if that's what's needed? And that's the process of an A3 project. This is a mnemonic downtime for things that we may do that are not efficient. And it's not all necessarily pertain to each project, each situation, each problem statement that you may create. But I thought it would be a good overview to point out. Sometimes defects occur. We spend time doing something incorrectly, and we rework and redo. So inherent inefficiencies. So in my particular case, if we have poor documentation, someone else has to go and look at the data, look at the chart, figure out why a certain medication was or was not prescribed. So an opportunity to improve overproduction, doing more than what is needed or sooner than is needed. So timing is very important. And finding the correct balance is important. Waiting. Unnecessary delay for resources, information, or equipment. I think that speaks for itself. Something that's a little bit less concrete, but very important, non-respectful behavior. So sometimes how people interact, just staff, co-workers, etc., may lead to problems and behaviors that are not acceptable or desire to work can create some of those issues and inefficiencies that need to be improved. Unnecessary movement of information or things or customers. So again, we have electronic medical records these days, which should streamline what we do, how we do it, and data entry and gathering. And I think sometimes it bounces down, and I think, and I will show you soon how we implemented a solution that we improved that. We implemented a way to make it more efficient. Inventory, so supply excess or lack, cause issues. Motion, unnecessary movement. If you add too many steps or take some steps away and have too few, inefficiencies arise. And excess processing sometimes may cause some of these problems as well. So I'm going to segue back into our project and what we found. So in the process of finding our root cause problem, our internal audit and investigation suggested that we had poor ranking in this metric due to deficient documentation. I think that the bottom line is that physicians are busy and the medical record is overwhelming and we're seeing more and more patients. And busy physicians don't always document comprehensively or efficiently. And there was a disconnect here between documentation by physicians and those gathering the data for the NCDR. And our abstractors and data collectors relied on these unstructured notes. And sometimes we're not able to figure out, one, patient was on an ACE inhibitor or ARV. Two, not prescribed but due to medical reason, just wasn't clear. Three, not prescribed because patient request or desire. And for the integrity of the data, they defaulted to option four when none of the other three were clearly documented and supported in the patient's chart. And we concluded that our root cause problem was the problem with this documentation and poor documentation. So our solution to the root cause problem was to integrate improved education and technology, specifically in our EMR, in our electronic medical record. We created, at discharge, a heart stop in Epic, which is what we use, where all cardiovascular medications on discharge are documented. And basically, we allowed the same four options, one, taking, two, not taking due to medical reasons, three, not taking due to patient preference. But four, not taking no reason, wasn't an entry. It wasn't an option. It was a heart stop. And therefore, at the time of discharge, clinicians are thinking about this and not allowing that important fact to fall to the wayside. And we use a multidisciplinary collaboration of physicians, statisticians, IT colleagues, where we created this queryable smart phrase with all these required fields, and we rolled it out. And we thought this would solve our problem. And then we studied to see how the result changed. Our results were staggering. We essentially jumped to 100% compliance with this measured metric and have remained there for over two years. We added a navigator to audit, re-educate, and implement adherence, so a gatekeeper to keep this process flowing. Again, part of the future state, what are the countermeasures, and how can you sustain them? And we thought that a navigator would help that. And we also found additional benefits, which we didn't necessarily initially set upon. We improved efficiency and accuracy in our data collection because we used opportunity not just to document ACE inhibitors and ARBs, but all other cardiovascular medications. So we have a vast database of hundreds and thousands of patients now being discharged and what they're taking, and we can use that for future studies, adherence, et cetera. We didn't just increase a measured metric. I think we made a real difference. We changed the value based in healthcare benefits, and we did that from both a patient's perspective and our provider physician institutional perspective. From a patient perspective, their discharge on guideline-directed medical therapy, these are classes of medications associated with improved outcomes and decreased major adverse cardiovascular events, and therefore patients are better off and getting more value in their healthcare. And also from our institution, we established that we are practicing guideline therapy. We are ensuring the best practice and outcomes for our patient population. And as I mentioned prior, we are expanding our data and research capabilities. So thank you so far, and I'd like to conclude with my presentation and summarize that we had an outlier in a measured metric, and we wanted to improve that. And I think the hardest and the most important step was the root cause analysis because it's hard to self-reflect and assess what you're doing less than optimally, but we found that in our particular case, charting and data collection was the inherent problem. And we rolled out a technological solution. We integrated it into our electronic health record, EPIC, and we became 100% compliant with this important measured metric. I think this shows you the importance of the NCDR's data because I think we didn't necessarily know that it was an area to improve with potential outcome benefits to our patients. So it gave us a picture of how we're doing and a metric that we can assess ourselves, both before where it needed help and now that we have solved it. And we were able to leverage this data with improved technology, education, and significantly improved compliance, and therefore much better outcomes. So once again, thank you. And the next slide will show my colleagues who supported this project.

quality improvement process

NCDR device registry data

prescribing yeast inhibitors

low left ventricular ejection fraction

ICD or CRT defibrillator implant