Good afternoon and welcome to today's event knowledge. Transparency and data is the topic, it is my pleasure to welcome you to today's event. My name is Victor Gonzalez. I am a quality improvement specialist with TMF, and I want to be sure that you are comfortable. Uh, joining us today, and then you make the most of your experience. Here's a couple of slides. If you joined early, you've seen these already, but we want to cover them to make sure that, uh, you have the best experience possible. chad's gonna be wide open. We want you to participate there if you joined us before, you know, that's our style. We're gonna be asking you to provide some feedback answer questions and make your comments in chat. We'll also be delivering some information there, uh, for you as well. So that's going to be found in the if you don't see it in your participant. Participant panel, which is located on the right hand. Side of your screen. You'll see the chat bubble down at the bottom corner and click on that. It will add it to your panel and you'll be ready to roll with chat. Without further ado, I'd like to welcome our friends from safe and reliable health care. Dr Don Karen we and Jeff Dunaway they definitely deserve a longer intro than what we have today, but they've asked me to keep it short. So I'm gonna do my best. We'll go ahead and get started with Dr, candidly. He is a senior HR expert. He is a physician leader who has focused half of his 35 year career on improving the quality and safety of patient care after medical school and residency training. He served as a full time faculty member in the Department of internal medicine. At University of Texas, South, Western medical center, where he taught students and residents and did basic science research he brought the concepts of patient centered disease management in the redesign of ambulatory care for 20,000 patients in the parkland health and hospital system in Dallas, Texas seeing both the power and failings of healthcare led to executive work at the Baylor healthcare system where he developed office of patient safety, that oversight, diverse portfolio of programs across its 12 hospitals and 100. And 100 ambulatory care sites, you contributed to the national literature related measure, measuring injury during inpatient care, and guided a variety of other quality and business intelligence activities at Baylor as its chief quality officer after leaving executive work. Dr. Kelly has spent the last 3 years sharing lessons learned with consulting clients, committed to the journey of delivering care that we all want for our own families. Don, received a BA, from Harvard College and empty and PhD degrees from Washington University in St. Louis. We also do internal medicine and residency. He has published 50 papers or book chapters received a variety of awards, served on federal and regional advisory committees, and served as a founding board member of 2 patients centered nonprofit organizations. He's joined today by Jeff Dunaway. Jeff joins safe. And reliable in March of 2020, and has a primary focus of supporting a variety of healthcare organizations on their journey high reliability he has. Practice is a registered nurse for 2007 years with the last decade dedicated to the high reliability and continuous improvement. He holds a black belt in lean 6 Sigma from Villanova University and a certification in change management. Jeff is passionate about helping healthcare. At both a national and local level through the empowerment of frontline workers and training of executives. He brings a servant leadership model to all of his engagements. And as a deep understanding, that culture eats strategy for lunch every time. Well, I appreciate that. And thank you gentlemen for joining today. I'm going to turn it over to you and we'll go ahead and get started. Next next slot, so my partner Don, and I will attempt today to. Give you a greater insight into the importance, uh, that transparency and data have in this work. And as we move through today's presentation, I just challenge you to apply a lens of self reflection. Uh, so you can better plan forward, uh, for your own next steps. Next slide the goal of any high reliability organization is to have its humans and its systems interact in a manner that's failure free and stable over time. Look for this goal to be realized, and its clinical operational and cultural spaces. This is achieved through being mindful, not in having your mind full. That is to say. That there's a situational awareness, uh, as opposed to a Pre occupation or tunnel vision, as it relates to the bigger picture. We want our leaders and our front line to have a state of mindfulness around the bullet points that you see on the screen. When we achieved this, it, it manifests itself in this way. We're preoccupied with failure. We have a reluctance to simplify. We have sensitivity to the operations. We're committed to resiliency and in all things we give deference to expertise. Let's look at the next slide. Here you see the, the 4 domains of the framework for high reliability. Last month's HR webinar was focused on teamwork and collaboration in the culture domain. Today were centered around the knowledge domain and more specifically transparency and data. The next spot, so again, our goal is to describe a perspective, uh, towards transparency and data in service of achieving highly reliable systems of delivering service, both clinical and nonclinical. And at the end of this presentation, we hope that you spend time again in reflection of your own organization and practices to assess alignment with this domain of the framework for high reliability. Next slide so it's no coincidence that transparency. Sits adjacent to culture in the domain for, for, uh, for the framework, because it's impossible to have transparency. Uh, unless there's a culture that treats people with respect values, their input and ensure psychological safety. And in the reverse, it's impossible to have a healthy culture unless the attributions of that culture openly discussed and evaluated. So, what is transparency, uh, it's the quality to to make possible or known or to make, um. Visible transparency is a visible outcome of your invisible motives. You want to not had or hold back. In an expert from his book, making healthcare, safe solution, leap States, a greater. Transparency throughout the system is not only the ethical ethically correct but will lead to improve outcomes, uh, fewer errors and, and more satisfied patients and lower calls but. To create, transparency does take courage and we. Often, see that, um, manifested, uh, in. In our, uh, leap frog scores and our data that we send that don's going to get into just a little bit later. Uh, I want to just take a few more minutes to talk about the importance of transparency and, and the ways that that we can use transparency. Let's look at the next slide. So, transparency involves operating with integrity and honesty, sharing data, breaking down silos, publicly recognizing when teams are transparent and using tools that enable transparency to create high reliability, creating transparency isn't always easy. In fact, it, it generally requires a vulnerability, uh, and a bravery, uh, just like we discussed when we talked about. Community it takes courage to create transparency and take ownership and responsibility for building trust uh, so that we can learn, uh, improve and and make a difference together here on the screen. You see just a few, um. Of the ways that that we can. Be transparent with our data, uh, share, uh, our continuous learning together, uh, in the upper right hand corner. If you've taken the score survey, uh, you'll see, uh, that is a, uh, a visual representation of the data that comes out of the, the score survey. It's basically the, the voice of of your staff. We'll talk more about that towards the end of this presentation. On the next slide. So again. To to dig a little deeper. What is transparency look like in healthcare? Uh. In the chat, you all have access to the chat I like for you to, uh, put in ways that, that you and your organization are transparent with your data. Um, and and any challenges that, that you face, um. I encourage you to, uh. Share details if it's we display our hand hygiene data, uh, on our, our visual management systems, or or somewhere in our units. Um, we participate in late for all. We, um. In whatever way that, that you, um, participate in transparency through data I'd like for you to share that with us through the chat. No transparency among clinicians themselves. Um. Can can also be be a challenge, creating a safe and supportive culture for individuals and teams to be transparent and accountable to each other. Uh, and a place where clinicians are open and honest about errors within the organization. Joel says posting clinical quality dashboards on the nursing units. Exactly. Joel. Thanks Ronda said, participate in late for all. Exactly. Display performance data on clinical units. Yeah. Daily management systems, so it sounds like all are very well versed in in different ways to to be transparent. Um. You know, public publicly displaying measures, uh, that are used to monitor quality and safety is a, is a measure, uh, and a way that of being transparent, um, being mindful, uh, sometimes that people are a little hesitant to share that if they believe that they will be treated unfairly, uh, should the same errors be publicly disclosed. Ronda says challenges hesitant for nursing leadership to display huddle boards. We're public in view. Exactly. Uh. Don, what do you think about that, putting, putting this data out there in full view of the public where our patients and our families can see that? What, what. Does that work for you? I think that's a, a great point. Jeff and I think most, uh, organizations in units kind of go through a process of considering that. Um, I think they would like to do that. But they're a little worried that maybe, uh, you know, if they show data that are uncommon, that, uh, that that will undermine the patient's confidence in, in the care that they're receiving. And sometimes even risk management can be kind of worried about, uh, whether that might be a source of litigation. Uh, but I think the vast majority of organizations work their way towards a sort of sufficient comfort to put things out there. Because I think the public knows things aren't perfect. And so, what's up there that is uncommon actually tends to reinforce confidence of patients in the unit because it's clear that they're working on things and they recognize they're not perfect. And so I think the benefits far outside the outweigh the risks of, of poor displaying data. Thanks, Don, and and I completely agree with you our, our, our patients and our, our, the families are under no misconception that we're perfect. They know that there are opportunities for improvement, they know that we are working to get better. So when we use data to, let's just say, show that our hand hygiene is 75% and that. We recognize that's an area of of opportunity for us. Um, I, I, if I was the patient, I would actually have greater confidence in that unit, knowing that they recognize their areas, and that they're taking steps to to improve that. Mm, hmm, absolutely. So so, sherry, uh, Victor is it possible to let. Sherry unmute and speaks. She's got a lot in the chat that I'd love to hear more about. Sure thing, let's see if we can locate her. Thanks, um, in the meantime, sherry, we're going to work on mute if you don't mind coming off to to join the discussion. But you said that on your department, you use visual management boards and and you not only share patient safety and quality progress. But you also share retention data and how you're progressing with that. We'd love to hear more about that share. Your line is unmuted. You can go ahead and during the conversation. Good afternoon. Well, thank you for unmuting. Me. Um, and currently so I'm the manager of the, uh, an acuity, adaptable unit, and a medical surgical department, and a rule community hospital in Ableton. Um, we are part of a larger organization with, um, so we have, you know, all adopted visual management boards over the last, you know, couple years and we're really working towards being more. And lean minded 1 of the things we do, we, um, in the departments in both of the departments of mine, I've put up glass boards and inside of those, it's very, um, it's not super busy, but you just, we display our graphs on how we're progressing like month to month, and then some of them would be quarter to quarter, but what we've identified and of course, majority of us probably on this chat or on this call are used to seeing happy patient, happy nurses, happy staff, happy patients trying to not only just focus on having a good patient experience, but having also a good employee experience. So, instead of just posting data, that may show. Okay, we look really poor this month. This quarter also showing what are the action items that we are working towards not just as a leadership team, but that we are engaging our employees in as well to move forward for that. So, we update them monthly and we share it in the nurses station area as well. So that way it's almost like a huddle. And then we also bring it forward and weekly relay. And then also at my staff meetings. So definitely ways to not just post something. And hope it gets looked at, but just trying to engage staff and it is absolutely in the view of the patients. Thank you sherry and and talk to us about if any barriers, uh, or or hesitancy around the transparency of data in your organization. You know, maybe not today, but maybe early on in, in your, uh, in your journey. So, definitely, you know, initially, especially, um, I'm a newer nurse manager, this is about year 2 and a half. Um, for me, I've been a bedside clinician in the for about 12 years before I decided to take the leap of faith into leadership or more formal leadership. Um, and it is challenging, especially from the beginning to display where you may have poor performance. Um, however, I think that what we've done is really tried to focus on appreciative inquiry and celebrate those small wins. Um, even if it's 1% improvement, you know, you can only bang up on the staff, so to speak with your with your emails and your words, and your display, you have to find those positives and really celebrate where we are excelling and then try to just really work from that. So initially yes. Um, you know, Jeff was it is a little bit difficult to share how we may look for on a graph or poor for a couple of years. And when you start to see those upward trends, and those celebration staff really do get on board with that. And I found being appreciative of those successes in small wins has taken me much further than focusing so heavy, hot and heavy on those poor areas. Yeah, thanks, sherry. I appreciate you coming off talking to us about that. So, uh, uh, Victor, we do the same for. For Richard. Mm, hmm. Um. Just culture certainly do hand in hand and and. Uh, saying, here is, is the hesitancy of of. Using your event reporting system, um, because some people may feel like they're telling them themselves and and actually be be punished to have a negative in. Impact sure thing Jeff. Uh, I've got, uh, Richard keyed up and ready to meet him. I'll go ahead and do that. If you'd like me to. Sure, Richard, what's your name is. Thanks to the, uh, to the chat Jeff about this and event reporting is a tricky thing. And I think many people feel badly about using it and sometimes even organizations do it as a way to tell on people as opposed to, uh, doing things to learn. But the vast majority of the time event reporting is handled in a constructive way. We recognize everyone makes mistakes and to pretend they don't is silly, but we can't learn from those mistakes if they're not reported. And so a, as a result as Jeff alluded, there's a program really called just culture, which some of you may be have experienced. But it looks at the issue of whether it's anonymous mistake or whether somebody was, you know, in the extreme, trying to hurt somebody. And if someone's trying to hurt somebody, that's not. Okay. But if it's an honest mistake, it is totally okay. And it is really we don't want to have a lot of them, but we don't want to punish anybody and we want to learn from them. Great points dawn and we can try 1 more time. I saw a Richard. What is attempting to meet himself? We'll see if we can connect with him. Richard, go ahead your line is open, but we might be having a little trouble there. Richard. I do apologize for that. We'll, uh, help to. Try to work through that and see if we can connect with you a later time. We'll go ahead and move on. Jeff. Yeah, thank you. So so, I hope you can see that that that the, um, correlation and the connection between transparency and data is essential. Data in a vacuum or data in the dark what do you any good you've got to have a culture that's ready to receive it. Ready to embrace. It has the courage to say. Hey, we've got opportunities here, uh, to to work on. So, Don's going to talk to us about data. We've got a couple more slides about transparency, but I think you're starting to really get the, uh, idea of how important transparency is with this. Let's look at the next slide. And many of you have already already talked about visual management systems, you know, we enable internal transparency, uh, but by using such tools, like whiteboards and and lens and Gimbel boards and other visual management systems, this encourages BI, directional communication and promotes, uh, people to participate and engage and discuss this information, um. And and we do this with the goal of learning and improving, you know, visual management systems can create transparency during specific activities, such as walk arounds and Huddles and and debriefs. Um, so there's a lot of opportunities, uh, and, and different, uh. Modalities to to be transparent with our data. Let's look at the next slide real quick. So, transparency between clinicians and patients exists when when patients and families are supplied with reliable information and in a form that's useful to them. Um, truly understanding all the plan tests and treatments and calls and and giving their consent to be treated. You know, patients are using this transparency in the medical community to make informed decisions about where to seek care, uh, CMS star right? Rankings and elite for all scores. Are enabling the public in a way. At an unprecedented level, to to make, uh, these informed decisions about their health care. Let's look at the next slide. It may be an opportunity to just think outside of the box to, uh, to find ways to, uh, to learn from others. And also to, uh, to to grow your transparency. Let's look at the the next slide. So, as leaders, there's an increasing need to think about transparency as the right thing to do to build trust with those that that we serve and the teams that we lead, and it takes courage to be publicly transparent because it can be challenging, um, concerns about litigation reputational calls the accuracy, uh, the ability to interpret the data, the comprehensiveness of of safety measures um, additionally national ranking systems and websites, including leapfrogging U.S, news and world reports share a few common scores and often generate things that can sometimes be a little bit more confusing than than the clarity that they create. Um, the next section of of presentation is centered around the data and, and Don is an expert in this field and he's gonna help us to understand, uh, with the foundation that we've laid around transparency, the types of data that that could be our best friend not. You bet thanks, Jeff and I put a couple of some questions in the chat I hope people will think about because there are things that you as important. Uh. Members of your respective organizations can be using data in a variety of different ways and encouraging its value because the data isn't timely if it isn't accurate. Um, is it hard to understand? Because there's too much of it. Those are things I'd like to sort of, encourage you to be thinking about and perhaps we'll talk a little bit more about those towards the end. Most people's impression about the topic of data is that it's kind of dry and boring. But, like, a building data is a key part of its foundation and when it's poor bad things can happen. Like, that condo collapse in Florida for me the last 40 years is a great example of do 1 and today each 1 because really, I didn't know all that much when I got started. But I've learned a great deal over time and I'd like to share with you that I actually enjoyed my assignment to develop a business intelligence team in the past. It was no 1 else wanted to do it. And so I got sort of assigned to that. It's not, because I'm that graded all this, but today, my goal is to fill in any gaps in your data foundation and to make it interesting and powerful and useful too. So, let me share with you a concept, uh, that, uh, it's not illustrated here. Let's go to the next slide and, um, but it's something for you to be thinking about and it's what we call the data information knowledge paradigm and what I mean, by that is data is just a tiny chunk of things, but when you put it together in meaningful ways, it gives you actionable information and then through action, we then generate knowledge through the things that we do based on actionable information. So, data becomes information when it's understood over time, or it's compared to other data so that it begins to point to a needed action or decision for example, patients, fall rate with injury or 100 beds is lower than the national, average of similar units. Well, that tells you something, right? That's information. That isn't just what's the full rate? It's, there's some comparison to it. The number of new nurses per bed, and then unit hasn't changed in 2 years. Well, that's a piece of information. We're not sure what we can do with it, but it's helpful. Another is the unit spent 300 dollars per patient, less than the national average, and is 20% better than it was last year. That's a robust piece of data. That really is information because it's now actionable. These are examples of what we call metrics or measures, and that term can be used interchangeably. And usually it's something per unit time or something for some other unit. When we analyze information of different types of dimensions that generates knowledge and the data information knowledge paradigm, this unit is doing well in safety efficiency and staffing and that's really transforming forming the data into knowledge. And and that's the kind of thing that's done in learning organizations. And you don't need to be a statistician to do this, just someone who can use Excel to organize key data and a few simple calculations and present the graphical you can tell a story. So let's move on again to the next slide. And, uh, here, we have illustrated some, some data, and let's talk about what we refer to as systems s, a system is a set of processes that generates a targeted outcome here. Let's think of each thin line as being time going from left to. Right and the vertical bumps representing when a say morning measure delivered to a unit, the higher the bump the more is being done the value or number starts rises and falls and then the process ends each day. On the left, you see, that this process is consistent every day and so we say that the system is stable on the right you see, that morning meds are delivered earlier Sundays and later others this is an unstable system, which makes it hard to predict what will happen for any given day and is more typical of the units that we encounter. The next slide will let us look at data in a way that tells us even more. Here you can see, I'm sure many of you have seen graphs like this, that analysts have shared and we call this a run chart. It shows the percentage of patients who left without being seen on the Y, axis in each of 52 weeks, the X axis and this gives us a sense of whether this there is a trend. And you can see that. There really doesn't look like very much of a trend. Um, the central tendency of this metric is shown by the dash line, which is the median, which is most people are have more experience with the mean, which is the average. But the median to remind you again, is that you remove the highest and lowest values until you get to the last 1 and that's the medium for this. Or for this metric. It's about 10%. It's usually pretty close to the main or average, but new on this graph, or are some lines called the upper and lower control limits are 95% control limits. This these are calculated. Statistically you don't need to have to know how to do this. They're done by your your analysts friends and can even be done on Excel without too much difficulty. And what it does is it tells you whether there is variation falls between these lines, which we call s, uh, the, uh, common cause variation. You see the number changes. Every week, but it pretty much goes up and down around the medium. On the other hand on week, 24, we have a value of 20%, and it's above the upper confidence limits. So, we can be pretty confident that something special happened during that week in the, or perhaps an error was made in measuring it on week, 24. so, this value is statistically inconsistent with the pattern of other data points be patient. Next slide so now when you get something like this, what do you do about that? Oh, no, let's go back. I'm sorry. Thank you, um, we'll talk about tampering in a minute. When when you see something like this, it makes you wonder how I wonder what happened there because that is, in fact, special cause variation and, um, the 1st kind of date tampering is called data tampering, which is actually changing of value. And sometimes it's justified. If you went to the unit and you found someone made a mistake and divided by the wrong denominator, then it may, you might find out that the number was wrong. So, you need to revise the run chart a 2nd, and more comp, common situation is called process tampering when we decide to change the process to when we think is better to decrease left without being seen when we do this, we hope to see a downward trend in the line, but when we do that, we're going to see an increase in variation the upper and lower confidence lines are going to get further apart. Okay. Now, let me shift to again to somewhat more practical things that I've learned in my career in presenting data. And the 1st, and I've learned these, unfortunately, the hard way, oftentimes, by doing things that got me into trouble. So my goal is to keep you out of trouble, the 1st is to not present data until you've thoroughly reviewed it and analyzed it or had somebody analyze it because being familiar with it is really important, don't present data to a group. When the leader of that group hasn't yet seen it. What did I learned that? The hard way with some data some data and the chief, and seeing that data and he was never doing that again. Uh, the 3rd is to be succinct. More data is not necessarily better. And also key is don't ignore data that conflicts with your biases, or hopes. Developing a reputation for sort of sort of spinning the data is a bad thing. What you really want is everyone to be thinking that you're presenting the honest truth in a succinct way, whether it agrees with what you hope it to show, but it's going to be it's going to be accurate. Now, before I move on, I'm going to talk a little bit about something called trend analysis and when we see points like this, and we make a change, we're hoping that those numbers are going to go down. That is the left without being seen. Maybe, we're going to do something to make it better and there are some rules for being able to tell whether or not a trend is significant without calling in your statistician. And these are very useful. And I'll repeat them. But the 1st is, is that if you have 6 consecutive points all above the medium or 6 consecutive points, all below the medium, then that's statistically significant. The 2nd rule is that if there are 5 consecutive points, each 1, a little less than the previous 1, no matter where they are related to the medium. So, 5 in a row where the change is all in the same direction is statistically significant. So. We'll we'll shift now the next slide I think we'll get a little more interesting and it has to do with quantitative and qualitative data. Since we're focused on changing culture to drive clinical improvement, we should focus on both quantitative and qualitative data as the quote on the bottom says to see the clearest picture of where things stand and using both stories. And data is much more likely to convince people that the change you're hoping that they'll make is worth their effort. Quantitative data or objectively measured, and there are things from survey results on, like, on the left and the spider diagram to clinical outcomes and financial outcomes. They tell us the, what? When where? And how many. But qualitative data are subjective, and they're collected in interviews, narrative, descriptions and focus groups. This kind of data helps us to understand the, why of quantitative data and it moves it from data to information. Oftentimes things you can do something about, for example, the comments section of the score survey is really important, because comments flesh out organizational strengths and challenges and often clarify which improvement goals are realistic and which specific projects are more likely to succeed. But quality qualitative data is often time consuming to collect, but it is often worth it. Let me give you an example. I was working with a hospital and before we did the score survey and debrief that's quantitative data. I arranged 620 to 30 minute. 1, on 1 calls with the senior leaders to address, just 3 questions, what are the organizations strengths. What are your goals and priorities? What's difficult for the organization to do? These short conversations, individual conversations at when added to the score data, provided me more confidence about which safe and reliable strategies and tactics would be easier versus harder to do and which hospital leaders might be allies and champions versus barriers for our work. Together these 2 forms of data were converted to actionable information. This is an example of the data information knowledge paradigm. Excellent. Okay, so, when we refer to as Jeff mentioned this earlier, and I'm going to repeat, I'm gonna underscore what he said. And that is we've been mostly focused on 1 of the 3 important domains culture, and we provided you with culture data but via the survey. But to have a sufficiently clear picture to succeed, we must measure review and improve performance in the 2 other domains. And those domains are clinical outcome data and they reflect the clinical impact of care. The tells us we should use the acronym steep with an extra E to describe components of high quality care. And those are care. That's safe. Timely effective, efficient, equitable and patient centered and this was a defined more than 15 years ago by the Institute of medicine. So, let's get and I'll go back over that in just a 2nd, but let's give some examples when you track in each of the areas of Steve, you know, you're covering what's important in healthcare an example of safe is injury rates. Uh, the fraction of sepsis patients getting 3 hour treatment bundle is timeliness. Antibiotic stewardship is effectiveness. Same processes of care for all races that's equity. Length of stay for uncomplicated total hip replacement is efficiency. The percent top box on H, caps would recommend is patient patient centered. So, again, going back to what were those 6 elements of steep air care that is safe. Timely effective, efficient, equitable and patient centered uh, so keep those in mind. And if your organization isn't really sharing information on all of those areas, it's important that they do. And when you're in a union, you might ask, are we really showing information that is actionable in all those domains? So, operational data for a unit, or whole hospital often focuses on describing resources, used to provide care. Now, moving into from clinical outcome data to operations data. Common metrics are relate to utilization efficiency and finances such as. Bed occupancy, staffing levels overall, Medicare, length of stay operating margin, cash on hand and these may not be necessarily things that you have to do something about. But they're very important, especially for the leaders to consider when they're trying to have an effective portfolio of programs to keep the organization due. Achieving its values and goals. So, an organization should be viewed from all 3 of these perspectives, culture, clinical outcomes and operations data and decision should be data driven. The hospital was strong finances, but poor quality probably has been well managed, but as a business, and it has it's proper if it's weak in culture and clinical improvement organizations, like, this are vulnerable to losing both patient, volume and staff by having values. That are at odds. With patient and professional values. A suggestion for success, find a win win project or 2, that will improve 2 dimensions at the same time. That is a clinical, operational and cultural, a couple of examples that were really big successes that I was able to participate in the 1st was engaging physicians in supply chain decisions. Uh, they, uh, you might think they wouldn't want to do it. But when we provided the incentive that we would be able to renovate the a little sooner, if we could save some money, the physicians, red lead, uh, jumped in. So that was being able to improve both efficiency information and, in fact, getting more consistent care through consistent components of the supply chain when we, uh, worked with the surgeons to, uh, and the chief operating officer. He said, you know, it isn't that we really shouldn't be just focused on every nurse being busy every minute, but we should have this. The surgeons work with scrubs and circulator they know better. Well, it turned out that that generated better clinical outcomes and it save money. And reduced readmissions and the overall time of surgery so that was winning in, uh, more than 1 direction. So, if you can find 2 or more directions or domains that you can find wins, when you're much more likely to be successful next slide. Um, and, uh. You might ask well, what do we mean by this question data for learning means the data are used only to improve and not to blame anyone or any group for sub optimal performance. At the organizational level data, for judgment, can help leaders know where they are, where they are doing compared to their competitors, like CMS, 5 star, for example but data can be judiciously, used to generate stamp awareness and motivation and the spirit of transparency that Jeff was talking about this helps us let the organization know that perhaps they're not just. terrific in some area but the goal is to be making improvement and the goal is not to be trying to shine the light of accusation on anybody but rather to be generating energy for change When looking inside the organizations to individuals departments, units and teams, we should use data to improve and avoid shaming that can shut down learning by reducing motivation to participate in requested improvement work and frequent criticism can cause the best staff to leave. Uh, but internally transparent comparisons can also be productive when we are sure they're used primarily for learning and improvement and not judgment. I also want to point out that 1 has to be a little careful about data for praise, because it can be a 2 edged sword compliments that focus just on a few people, or units can create resentment, spread out your praise. That's the lesson. There's all nearly, always something positive that can be said. About any unit or any person so next slide and I'll turn this back to Jeff. Thanks, Don, and as always just just wonderful. Always learn learn from you just to, uh, start to wrap up the data piece thinking about collecting information in real time. It's so beneficial, because you can spot defects early before they really could harm anyone. And and we know that, uh, in in organizations and through high reliability, we understand that humans are going to make errors. The idea is to keep the harm or the errors from reaching the patients and the earlier, we can understand the data. The, the better we're positioned to prevent that harm from reaching the patient. Um. you know understanding defects when they're small it really lets us get out ahead of of it uh before it spirals out of control So, let's look at the, the next slide. So what we want to, uh, talk to you about it and lead you with is as a reminder some of you, uh, have opted into participation in the score survey last year. Uh, everyone who is enrolled in this program. Uh, has the same opportunity this year. Uh, so if you did not participate and you would like to to, uh. You you may have armed that, that your culture believes there's a problem if anybody. Uh, is participating today that that did participate last year and you want to talk a little bit about the data that you received, or about the process of the survey uh, I would encourage you to put it in the chat or or simply put your hand up electronically, uh, so we can hear from you. Uh, this is a wonderful tool to start to understand some, some of the, um. Qualitative aspects, uh, that that maybe it's hard to put your finger on but, um, Don Don helped me out here. We can actually have hard data around things that are hard to put a a number on the. Oh, absolutely I, you know, I think 1 of the things that, I mean, there are some, um, items in the survey that I think are phenomenally helpful. Uh, 1 is has to do with whether or not the people. There's a question that says, I would feel safe being treated here as a patient. Well, I can tell you that that that item was the most powerful predictor in. About whether nurses. You know, gathering the data and understanding what it's telling you. It's really only half the equation. Um. Uh, I do want to plug the the window for the next score survey will be made through August. Uh, there's a process of prep work followed by an open window of time where the surveys administered, uh, W, with analysis and sharing of the data towards the end of that window. But but having the data is only 1 piece. Let's go to the next slide. Um, over the next 2 months, uh, Don, and I will be bringing you the learning system domain of the framework, uh, where we can really start to, uh, discuss the learning system and and improvement, uh, broken down into, uh, the sections of improved learn and implement there. There's so much material to cover that that we're breaking it into 2 parts. Uh, and we'll be talking about that in April and may, um. Done in, in the last couple of minutes, there was 1 additional question about just culture. Could you just talk about that a little further and and how it relates to high reliability and, uh, any suggestions or? Um. Any, uh, resources, you know, of that, that people can latch onto. Sure. Well, they're, uh, well, 1 can go out to, uh, uh, the web and search for, uh, just culture and there is a, a site called, uh, called the just culture community. Uh, it was a, that was a concept that was, uh, promoted by David marks who's who's also a Texan and, uh, and so, uh, the idea is really that a culture. That is just, uh, evaluates the nature of a mistake. Um, and if a mistake is, uh, because somebody, uh, you know, came to work drunk, then that's not okay. And so that. So there's an algorithm that actually exists. So that when a mistake happens, 1 can go through an algorithm to ask questions. Like, did the person do this on purpose was the person knowingly impaired, uh, was the person unknowingly impaired and perhaps that person, then would need help in order to make them safer to deliver care. And so, as a result, it goes through a series of fairly straightforward questions that you can ask about the person who made a mistake. Um, and, uh, that resulted in some sort of a a bad outcome. So I would strongly encourage it because, uh, pursuing this. Provides a great deal of relief to the front line staff because if the staff know that they're going to be judged using that, then they think is fair and commonly this is referred to as a fair and just culture. So, as opposed to something bad happens, we got to find a scapegoat. Because, uh, suddenly the news newspaper got wind of this or something like that. And so, uh, it's a, it's a really valuable component for organizations to be considering and then doing. So, it usually is a partnership, not only with clinical leadership, but also with, uh, with risk management and, uh, because they have to be okay with it. And HR, uh, because it's really a philosophy and practice took that, uh, is, uh, active in all 3 of those areas. Don, don't you also find besides building confidence and, and, uh, uh, employees of of how they will be treated in case of an error? It also builds confidence, uh, and and the, the leadership, because they don't have to guess, how am I gonna approach this? You know, it's it's very absolutely. You know, and so because in a sense we wanted to acknowledge we weren't perfect, but what we were doing was committed to getting better. So so great question, thank you for, for asking more about just culture. We, we. I love it it, it incorporates cleanly and very well into our, our high reliability, uh, presentations. Uh, we can think more about that in the future if, if that's a a great need, uh, or a desire to hear more about that. But again, the next 22, uh, presentations, uh, April, and may will be around the learning system about how to improve and learn and implement. So, we're excited to bring you that. Thank you for your engagement today. Thank you for your attention for, for your presence. Uh, Don, and I love bringing this material to you and Vanessa or, uh, Victor. Please turn the rest of the time back over to you. Yeah, that's just like to add to to jeff's, uh, just a bit, which is to say, we really appreciate this people being active on the chat. It makes it, I think this makes it a a more comprehensive kind of interaction where we can really make sure we're providing value to you. So thank you for your willingness to do that. Really appreciate it. Couldn't agree with you, gentlemen more. I do appreciate you sharing your expertise around the subject. I've dropped in a link into the chat, uh, that asked for just some, uh, uh, quick feedback on the event. And, and your experience today would do appreciate it as you disconnect. You'll be redirected, uh, just follow that link. We do appreciate it again. Just a couple of things before we part initially. Uh, maybe a couple of minutes for some questions. If you'd like to ask another question and chatter and you have a comment. Go ahead, and drop that in, uh, all of the information, including this recording is gonna be available at TMF networks dot org. If you're not already hooked up, be sure to do that travel over there. Um. Go ahead, and explore all the resources that are available to you many of you have and we do appreciate that. You want to work with us in the team of quality, innovation network uh, you can go ahead and do that set up your account. And take a look follow us on Facebook and Twitter, and you can do that there at the links provided. Debra in the in the chat, I, I think, uh, be addressed that earlier in the chat victor. B, if you want to copy of the slides. Sure, absolutely. So it's going to be on TMF networks dot org. I think B, if you could drop some additional information there, we can definitely. I'll go ahead and connect with Deborah and make sure that she's got that uh. Um, ability to see that. Thank you, Vanessa. I appreciate that. Again. We do appreciate everybody sharing their time with us today. Hopefully you've, um. Taken away a few nuggets provided to you by Dr Kelly and Jeff. We appreciate it again. Thank you so much to our partners with safe and reliable. We look forward to hosting you again in the near future. If you need anything please feel free to reach out. We'll be happy to connect with you and hopefully, um, meet your needs that way. Well, that doesn't include our call for today. Thank you, Jeff, thank you. Dr. uh, we hope that you have a fantastic rest of your day. You may now all disconnect.