NTSP Specials (Season 2): Professor Tracy Finch on Improvement Science

Tracy is Professor of Healthcare & Implementation Science in the Department of Nursing, Midwifery & Health, Northumbria University, UK. Tracy’s research focuses on how we can understand and support the implementation of complex interventions in health, care and wellbeing. Tracy is known for her work in implementation science, most notably Normalization Process Theory (NPT), of which she is co-developer, and for developing tools and assessment instruments to support non-academic users conducting implementation work in practice settings.Tracy was part of the team leading the Improving Tracheostomy Care program in the UK. Tracy spoke at the 6th International Tracheostomy Symposium, held in Manchester UK, in October 2021. This presentation is an extract from that meeting.

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Transcript

SPEAKER_01 0:25

But now I'd like to introduce our first speaker in this session, who is Tracy Finch. Tracy is Professor of Healthcare and Implementation Science in the Department of Nursing, Midwifery and Health at Northumbria University. She's known for her work in healthcare improvement science and co-developed normalisation process theory, which I believe she's about to uh give us a lowdown on. She was also instrumental in analysing healthcare professional engagement during our improving tracheostomy care project.

SPEAKER_02 1:01

Good evening or good morning, everyone. It's a pleasure to be here, in part on behalf of Northumbria University and also in my role as knowledge mobilization and implementation science theme lead for the NIHR-funded applied research collaboration in the Northeastern North Cumbria. So hello from Newcastle in the northeast of England, partly known for a bridge that looks a bit like the one that you might find in Sydney, Australia, and maybe less known for our amazing beaches. And that picture there is what a Time Mouth Beach drawn by my daughter. And so my aim today is to bring some implementation science perspective to the problem of how we get good ideas into practice when we're trying to change things to improve care. And implementation science has developed over perhaps the last 15 or more years in recognition that this is an important area in and of its own right in terms of scientific study. And the focus here is on really generating knowledge of how we can do this implementation work and embedding of interventions into practice better so we can ultimately improve health. And implementation science is based on the premise that in order to improve health and well-being, we not only need effective care and services and interventions, but we need to improve the process of how they're implemented. And so we focus very much on this second part of the equation. As a science, much of our work is underpinned by theories, models, and frameworks. And we've seen a lot of these approaches develop over the years. They all do different things, you know, depending on what you're trying to achieve. Some may be more useful than others, which we'll come to. But a good place to start, if you're interested in finding out more, is to have a look at this taxonomy, which is one of the most well-cited and useful taxonomies that really sets out what these approaches are and what they do. So some of them will describe or guide the process of translating research into practice, so they might have more practical focus. Others are more theoretical, involved in understanding and explaining what influences implementation outcomes. And some of these are framed much more about how we evaluate implementation efforts. The use of theory doesn't have to be purely academic. And I hope to show you in this talk that there are some really practical ways that you can use theory for your problems of implementation. And choices can be guided by really what you're trying to achieve and the kind of change that you're making, and what sort of barriers and impacts you think are going to be relevant in that work. For example, implementation science approaches can help with planning and developing new interventions in terms of maximising their implementability. It can be used to evaluate interventions by guiding the kinds of questions that you need to ask and data that you need to collect. And they can also help in rolling out proven interventions by being used to help design implementation strategies. For the rest of my presentation, I'm going to focus mostly on one theory, normalization process theory. And this is a theory I've co-developed with Professor Carl May and a lot of other collaborators over the last 15 years, and it's become quite established and well used in the field of implementation science. And I like to describe normalization process theory or MPT as really just a way of thinking about implementation problems that focuses on two key things. Firstly, how do those interventions become part of everyday practice? And secondly, how did different groups of people need to work together to achieve it? So it's really about the collaborative work that has to happen around most complex interventions to improve care. So we break this up into four different areas of activity. We call them mechanisms, and we feel all of these are important. So coherence is about a new interventional practice making a lot of sense to those involved. Cognitive participation is around that commitment to being engaged and to staying engaged. Collective action is really where the work happens. How is this achieved? How is it achieved together? Who does what? What are the issues that happen and have to be resolved? And finally, and this is really important, there needs to be an element of appraisal work to be done. We call this reflexive monitoring. So, how do people appraise whether it's working or not, how it might be approved, and using those reflections to improve the process of an implementation process. And I can simplify this further just to say MPT is all about the work. What is the work? Who does it, how does it get done, and why did it happen like that? For the rest of the presentation, I'll illustrate some of these ideas around sense-making strategies and outcomes by drawing on one particular project that was undertaken to improve tracheostomy care across England. The Improving Tracheostomy Care or ITC study was a national quality improvement program with independent evaluation, and the project was funded by the Health Foundation but involving lots of key partners. The main results of the study are reported in the British Journal of Anesthesia, but the project involved 20 hospitals across England who were delivering tracheostomy care, and it was all based around the global tracheostomy collaborative that implemented bundles of quality improvement initiatives. The mixed methods were included service quality metrics, patient outcomes using the HADS and other measures, qualitative interviews with staff and site leads, focus groups, appreciative inquiry forms, and the Nomad survey, which I'll come to in a bit, as a measure of engagement with the quality improvement activities. So data collection happened before, during, and after implementation of the QI bundles. So I explained earlier that normalization process theory puts a lot of focus on what we call coherence, which is sense making. And a key element of any implementation process is to really do some work to make sense of the implementation problem. From there you can work out what it is that you need to do or can be done. In the ITC study, this was approached from a number of methods, but one of those was appreciative inquiry that used some forms that helped people involved in the different sites in the collaborative to respond to some questions so that the project team could really understand what the issues were that would need to be addressed. So this asked questions like what is particularly good about the care in your service, or what quality concerns might there be, what are the ideas for improvement, what's being tried, etc. And here you can see just some examples of the kind of issues that can be identified through undertaking this kind of data collection. And these refer to some of the issues or problems that have been observed across different sites. What I would say though as well, going back to the earlier slide, is there's also a focus here on good practice and identifying and sharing that as well. So it's more balanced, but this gives you a feel. So making sense of the problem is a key step. There are lots of ways you can do this. It could be survey data collection or it could be group discussion, really exploring barriers and facilitators to improvement. And from the implementation science field, there are a lot of things and tools that might be drawn on and used. From normalization process theory, we have an online toolkit which is basically 16 questions, and it allows you to make assessments and they help you think through the problem. And you can do that as an individual or with groups and explore issues that way. There are also lists of barriers and facilitators in all kinds of areas that you might also be able to draw on if you find something that's relevant to your particular problem. Building that understanding of the problem that we're trying to address helps to guide us much better towards the kinds of strategies that we need to develop. And in the implementation science field, there's been a huge amount of work done around strategies for implementing clinical innovations in practice. In particular, the work of Byron Powell and colleagues in the United States. And this gives you an example of what that looks like in the sort of categories, different kinds of strategies with a bit more detail around what they involve. This just gives you ideas, and there has been some further work to map those against particular kinds of barriers. So some strategies will be more useful for addressing certain kinds of barriers, and there's a lot of progress going on in that work. In the ITC study, this is what some of that work around identifying and prioritizing strategies actually looks like. So it might be a little bit small on some people's screens, but what we've got here is a list of quality improvement initiatives tackling different kinds of problems. And in the study, a really collaborative approach was taken to really unpack which ones of these might be more useful, more important, and you know, which ones were sites actually planning to undertake in their QI work in the context of this program. So you've got lists of interventions, but you need to do some work around, you know, which of these should we prioritize, which are most important, which will have the most impact, and what are we actually going to do. And the third key area I wanted to discuss here was around progress and outcomes, and in MPT terms we call this reflexive monitoring. And I think this, I think the usefulness of this is perhaps still a little bit underestimated, but I think came through really well in the ITC study, in that having data about, you know, about the interventions and what effects they were having was really helpful for improving care. So here we've got some quotes really focusing on how the fact that this data collection was systematized and how that really helped so that those involved could know how they were doing, if things were improving, uh, they could use that that data to keep moving things forward. And to go briefly back to implementation science more generally, a lot of really good work has been done around this notion of implementation outcomes. Um, and I refer here to Enola Proctor and colleagues' taxonomy around this, and and the diagram really shows there what when we talk about implementation outcomes, what are we interested in? It's things like acceptability, adoption, appropriateness, costs, etc. And it's a reminder that when we're doing uh any kind of research or even improvement work, it's useful to include these measures and assessments. One such assessment tool that was used in the ITC study, and which I'm going to illustrate a little bit more, is something called NOMAD. And NOMAD is a survey instrument that we develop directly from normalization process theory. And it's a survey that you give out to staff that are involved or any participants that are involved in an implementation process, and it assesses what is happening around that implementation process from the perspective of those involved, and it includes those four constructs that I've been explaining in relation to MPT. And just a very quick look at what a nomad survey might look like. It includes these questions and there's a scale for endorsement of those. But the key point is that a survey like this really has to be adapted to the context that you're using it in, and so you tailor the wording of the questions in terms of what they're referring to so that they make sense to those involved. And I'm aware that many of you who do use research instruments like to know that those instruments are validated. Um, we we have had uh good validation results from the NOMAD survey. This is from the original work showing that the concepts of MPT are supported with reasonably good psychometrics. It has been translated and validated in several other countries as well, and we're finding similar results, so that's encouraging. And in the ITC study, NOMAD was used as a measure of engagement. So, and I think that's quite a good description of what was being explored here. How well were the sites engaging with the QI bundles and the process over time? And over 1,500 nomad surveys formed the data set for this. And the findings in general showed that considering all sites together, aggregate scores increased significantly from baseline implementation to evaluation phases. There was some variability indicated by the red boxes there, where scores went down in some of the sites, but overall there was a positive shift. And another finding was that there was significant positive relationship between percentage change in Nomad in relation to the collective action construct. And if you remember, that is about the actual activity that people are engaging in and the work around making the intervention fit into their routine work. So there was a positive uh change in that over time. And I'd just like to also show this from the ITC study because it shows the different ways in which you might utilize some of these instruments. And here, what we see is uh what the team called a scorecard. So this was about ranking sites. So we've we've got 20 sites, and you'll see uh to anonymize those sites, I've taken the ITC study to be global, and they're now countries instead of hospitals. But what this shows is is an exercise in determining a ranking of what we might call overall success in relation to the project, which is based on the percentage increase that they got on their NOVAD score and the total number of interventions that they were implementing. And so this is essentially a ranking exercise, but which can be used to relate to other data that's coming out of the project. What I would say is the ranking is useful here because you're looking at here we've got 20 different sites and making those kinds of comparisons, and if you add that to other data, for example, the qualitative data coming out of the study, you can start to get a sense of not just who might have done better, but also why they have done better. So it does raise some questions though about what does successful mean in this context? Is it about interventions getting uh more embedded, or is it about people making a bigger change from a low baseline to a higher final position? And here a score-card approach might be useful and can be used in improvement research. So just coming to the end of this presentation now and rounding it off by bringing it back again to normalization process theory. And I really liked this quote from the qual one of the participants in the qualitative study, who really sums up what this improvement work is all about. You know, it's about talking to one another, sharing ideas, having that representation from all the different specialties and professions involved, and also about being innovative, looking at different ways of working, not being scared to do that, and that those are the ingredients of achieving good, safe care. So, as an approach from implementation science, what does MPT tell us about implementing and sustaining change? Well, implementation work is complex, it's messy, and it involves ongoing efforts to achieve that change. It works through building understanding of the work, establishing and maintaining the participation of those involved, and ensuring that participants and organisations have the means of appraising and adapting, reflecting on things so that you know they they can be approved. So thank you very much for listening, for sticking with this.

SPEAKER_00 17:30

Thanks to Tracy and the team for that fascinating talk. And we've certainly benefited from Tracy's insight as we evolved from improving track product. However, the views and opinions we discussed on the podcast RO and social media.