Speaker 1: Hello, and a warm welcome to this video series entitled Implementation and Scale-Up of Best Practices in Healthcare. My name is Zahira McNatt, and I'm the Director for Leadership Education and Practice at Yale's Global Health Leadership Institute. I'm joined today by Drs. Leslie Curry and Christina Talbert-Slagel, also of Yale's Global Health Leadership Institute, and we're here today to talk about implementation and scale-up of best practices in healthcare, and to explore a new model for helping us to manage the difficulties in this arena. Leslie, Christina, thank you so much for joining me. Perhaps we should start with getting to know a bit more about you.

Speaker 2: Sure. I'm a Senior Research Scientist at the Yale School of Public Health and a lecturer at Yale College. I'm interested in the development and implementation of evidence-based practices, innovations of all types that influence health and healthcare, and I use mixed methods in this work. In this project that we'll talk about today, I was a co-principal investigator with Elizabeth Bradley, also from the Yale School of Public Health, and we assembled a fantastic team of very diverse, smart, motivated, committed team members to help us with this project, so thanks for having us. Welcome.

Speaker 3: And I'm Christina Talbert-Slagel. I'm the Senior Scientific Officer of the Global Health Leadership Institute and also a lecturer at the Yale School of Public Health. My interest is in complex systems, how they work, how they change, and how they maintain the status quo. So first, what is a complex system? It's really a system of interdependent parts that are interrelated and they adapt to changes in each other, and occasionally complex systems exhibit emergent properties, meaning some sudden change in the entire system. So as you might imagine, that definition can apply to lots of different kinds of complex systems, including healthcare systems, hospitals, and also biological systems like the human body. So in working with the amazing team on developing the model we're going to describe today, we brought together a multidisciplinary perspective about thinking about change and innovation in complex systems and in healthcare. So I'm very glad to be here.

Speaker 1: Thanks. Fantastic. Welcome, you both. Well, Leslie, you mentioned the terms implementation and scale-up, and can you tell us more about what they mean?

Speaker 2: Sure, yeah. I think it's important to take just a few minutes to describe the terminology. Implementation is a deceptively simple word, maybe. You know, putting something into practice seems simple. The reality is we really don't do a very good job of this in healthcare. It in fact takes 17 years on average for our research to get out there into the real world and actually make a difference in caring for patients and their families. This for a lot of reasons. We produce lots of evidence, over 2 million published articles a year. Some of this evidence is ambiguous or even contradictory, and imagine the practitioner in the field who's just absorbing all of this data and trying to make real change in the world. And so implementation is about that process of getting that evidence out into the real world. Scale-up means different things to different people. There are lots of different terms for scale-up, spread, diffusion of innovation. People talk about it in different ways. I really like the definition offered by the World Bank, and this is that the process of scaling up is expanding, adapting, and sustaining practices, programs, and policies across different places and over time in order to affect large numbers of people. And I like it for a couple of reasons. It reminds us that the impact of the innovation is critical. We have to have successful innovations. Not everything should be scaled up. And it reminds us that we're not only talking about very narrow innovations or interventions in clinical environments. We're talking about large programs, system redesign, policies at many levels of government. And so I think it's a helpful definition for those reasons.

Speaker 1: Fantastic. Thank you. Well, there are hundreds, if not thousands, of these kinds of innovations, right? To help our audience understand exactly what you're talking about, can you give one or two examples? Sure.

Speaker 3: I'd be happy to. One of the innovations that we studied in the course of developing this model was an effort to address a need for patients who have a certain kind of heart attack from the time they arrive at the door of the hospital to have a type of cardiology intervention called percutaneous coronary intervention. So I'm not a cardiologist, but essentially that's a balloon inserted in an artery. Now if that happens within 90 minutes of the patient arriving at the door to the hospital, they have a much better chance of having good health outcomes. And sometimes it can even be life-saving. In 2005, less than 50% of patients who qualified for that procedure were getting it within 90 minutes of arriving at the door to the hospital. In 2010, more than 90% of those patients who qualified were getting that procedure within 90 minutes. So the innovation there was actually putting the practices in place to get door-to-balloon time under 90 minutes, and it happened in five years and spread all over the country. So we looked at that as an example of successful implementation and scale-up of a health care innovation that really spread all the way across the United States.

Speaker 1: Excellent. Thank you.

Speaker 2: Maybe I'll offer a really different kind of example, just to give you a sense of the range of environments and areas in which we think the model can be helpful. So a different example is that of community health workers. This is an approach using lay health workers who are often of a particular community, who have roles that include primary health care and health promotion, disease prevention kinds of activities at the community level. And community health workers may be volunteer, they may be paid. Models are different in different environments, but very strong potential to help with primary care access and quality in underserved areas all around the world.

Speaker 1: Fantastic. Thank you so much for sharing. So these innovations sound really exceptional and potentially beneficial to their communities. So what's making it so difficult?

Speaker 3: Well, so as Leslie mentioned, change in the system is really hard. And there's been quite a bit of study on innovation diffusion and why innovations don't take place. One of the reasons is that systems have evolved to maintain the status quo, to keep things the way that they are. And that can be a function of policies that are in place, the way that people work together in an organization. When somebody says, we don't do things like that around here, that's really maintaining the status quo and really resistance to change. And it's a normal part of a system that has evolved to exist the way that it does. But then that makes it hard to introduce change and have it stick and spread. So some of the reasons that we've understood for innovations to not succeed in making permanent change can be, for example, if an innovation is introduced into a system by a person or an entity that's unfamiliar. So organizations have boundaries and sometimes those can be physical, like the walls of a hospital. Sometimes they can be social, like membership or who works there. If an innovation is introduced into a system by someone who doesn't ordinarily cross the boundary, then the likelihood of it becoming part of the way things are done is very low. Another reason that innovations tend not to take hold is if they're conveyed in a way that doesn't make sense to the people who are supposed to be using them. So it may be something published in one of these millions of papers that Leslie mentioned, but it's in a language that people don't really understand, it's inaccessible. If it's introduced in that way, then people won't use it. They don't speak that language, it's not familiar to them. And then another reason that innovation may fail to stick, as we say, fail to be implemented, is if it doesn't become the normal way that people do things. This is well documented in lots of different healthcare innovations. Something can be introduced into a system, maybe a hospital, people do it for a little while and then it just doesn't become the norm and it doesn't stick and it's not permanent. So really, it didn't become part of the DNA of the organization. So those are some reasons why change is hard.

Speaker 1: Great, thank you so much. So the two of you, supported by, as you said, a multidisciplinary team, have created and developed this model, AIDID. Tell us a bit more about that.

Speaker 3: So I'm happy to give a brief overview, I know we're going to go into more detail. But the AIDID model, in essence, is a five-step model that is focused on understanding an organization or a user group, understanding the innovation that is being introduced, thinking about the environment around that user group, and facilitating implementation of that innovation so that it becomes a permanent part of the way that the user group does things. So there are five steps, as I mentioned. Assess, which is really understanding the user group, understanding its boundaries, understanding the environment around it, how are things working there, when change happens, how does it happen? Innovate, which is actually tailoring, now that's a focus on the innovation, tailoring that innovation to fit the user group. Develop, which is to address some of these environmental factors around the user group that may serve as facilitators or barriers for change. Engage, which is really a deep engagement with the user group to actually bring the innovation in, make it accessible to the people who will be using it, and work very closely with the users to make it part of the DNA of the organization. And then the last step is devolve, which is to spread the innovation to other similar user groups on existing networks. And the only other thing I'll just mention briefly is that these steps are really non-linear and interdependent. So when you're developing the environment, you may still be assessing it. When you're innovating to fit, you may be working to engage. So that's another major feature of the model.