7: WHEN you could have most impact


Perfect research which comes too late is no good for decision-makers. The importance of timing is often underestimated. The starting point is to try to ensure your research is relevant when it finishes and understand any important recent changes in policy or service landscape which may affect the way your results land. Some factors can be predicted, but researchers can also find ‘hooks’ that play research back into the issues of the day. Some examples are given of research which achieved topicality, including researchers studying the ‘weekend effect’ in hospitals and centralising stroke services. The use of interim findings and estimates of ‘lives saved’ at a critical point helped researchers to influence important decisions about stroke reconfiguration at the right time. Other examples on COVID-19 services show how researchers can be nimble in responding to rapidly changing contexts. Some international examples show how the readiness of the environment often trumps the quality of research in terms of impact.

The health economist Martin Buxton once said that it is always too early to evaluate a health technology until, suddenly, it is too late (Drummond and Banta 2009). This is particularly true for complex health evaluations, like workforce or service models. They need to have had enough time to have bedded in and be stable enough to ensure that the approach could be adopted elsewhere and the way it works is understood. But waiting too long for an innovation to ‘mature’ may risk that an evaluation comes too late to change practice. New approaches, such as models of integrated care models, hospices at homes or virtual wards became widespread often in advance of formal evaluations. Landing your research findings at the right time can be critical to how many people it reaches and what difference it makes.


Perfect research which comes too late is no good for decision-makers. The importance of timing is often underestimated. The starting point is to try to ensure your research is relevant when it finishes and understand any important recent changes in policy or service landscape which may affect the way your results land. Some factors can be predicted, but researchers can also find ‘hooks’ that play research back into the issues of the day. Some examples are given of research which achieved topicality, including researchers studying the ‘weekend effect’ in hospitals and centralising stroke services. The use of interim findings and estimates of ‘lives saved’ at a critical point helped researchers to influence important decisions about stroke reconfiguration at the right time. Other examples on COVID-19 services show how researchers can be nimble in responding to rapidly changing contexts. Some international examples show how the readiness of the environment often trumps the quality of research in terms of impact.

It’s all about timing

The health economist Martin Buxton once said that it is always too early to evaluate a health technology until, suddenly, it is too late (Drummond and Banta 2009). This is particularly true for complex health evaluations, like workforce or service models. They need to have had enough time to have bedded in and be stable enough to ensure that the approach could be adopted elsewhere and the way it works is understood. But waiting too long for an innovation to ‘mature’ may risk that an evaluation comes too late to change practice. New approaches, such as models of integrated care models, hospices at homes or virtual wards became widespread often in advance of formal evaluations. Landing your research findings at the right time can be critical to how many people it reaches and what difference it makes.

Thinking about the timing of research, it is useful to consider Kingdon’s ‘multiple streams analysis’ (Kingdon 1995). He argues that a ‘policy window’ opens when three separate streams of problems, politics and policy come together. Each stream has its own flows, blocks and momentum. But for policy to change, there needs to be a well-defined narrative around the problem; a favourable political climate; and a workable solution or policy. These can sometimes be nudged forward by what Kingdon calls policy entrepreneurs, those agents with knowledge and influence in policy worlds. These may be professional leaders, thinktank analysts or lobbyists who are connected well with different advocacy networks.

Mintrom (2019) has described the attributes and strategies used by the policy entrepreneur to advance causes or campaigns. While researchers themselves will not usually fall into this category – although some examples are given in this book of academics who are ‘energetic actors … to promote policy innovations’ (Mintrom 2019) – they may need to identify them. Finding out who are the movers and shakers in a particular field and working with them will help to identify the opportunities and windows for change.

What is the next hot topic?

In health research, much of the impact in timing outputs is down to the initial focus and relevance of the study. At the time of commissioning, the research funder and study team need to be confident that their findings will be meaningful and relevant in three to five years’ time when the project is complete. NIHR uses deliberative processes with stakeholders to identify and prioritise research questions in relation to the agendas of management, delivery and use of services. Which are the most pressing questions? Will research findings from completed studies still be relevant in five years’ time? Can we anticipate the problems and solutions on the horizon?

While the importance and urgency of research topics can be tested out with target audiences, it can be hard to predict the momentum of the political stream (in Kingdon’s frame). For instance, NIHR had identified 24/7 working in the NHS as one of the top uncertainties where more research was needed in 2013. This was one of the priorities identified in a series of surveys, workshops and participative processes with patients, managers, clinical leaders and researchers. A call was put out to researchers and a number of projects were funded.

The issue of providing specialist cover and services across the week had been an important operational issue for the NHS for some time. But researchers in 2013 proposing careful analysis of routine hospital admission data could not have anticipated how the ‘weekend effect’ would become front-page news, linked to disputes between the government and junior doctors on medical contracts during 2016. Indeed, an early academic output (Meacock et al 2017) from the research team studying admissions and mortality across the week became the subject of cross-examination for the Health Minister and Chief Executive of NHS England at a Health Select Committee session.1

With hindsight, we can see that seven-day working ticks a number of boxes for rising high on the policy agenda. In policy analysis terms (Hogwood and Gunn 1984), this includes an issue which has reached crisis proportions; achieved particularity (that is, is focused and understandable); is emotive and engages human interest; has wide impact; and raises questions about power and legitimacy. In this case, all these factors came together at a particular political moment.

Catching the moment

Chapter 6 showed how we now understand more about the messy and dispersed nature of policymaking. There may not be a single policy ‘window’ – instead, there will be ‘lurches of attention’ by decision-makers. What this means for researchers is being nimble, flexible and paying attention to debates and moments as they unfold. As Cairney and Kwiatkowski note (2017), ‘Their [researchers’] effectiveness comes from an investment of resources to generate knowledge of the political system and its “rules of the game”, build up trust in the information they provide, and form coalitions, all of which helps them know when to act decisively when the time is right’ (Cairney and Kwiatkowski 2017).

A good example of this was the NIHR study evaluating the impact of centralising stroke services in London and Manchester, led by Naomi Fulop (Box 7.1). The team was able to work with service networks and release findings at a time to influence planning decisions on the scale of future change. This example shows the impact of early and sustained engagement with clinical and service stakeholders as well as stroke charities and patient groups throughout the study. Promotion activity included a series of imaginative and participative seminars with service leaders, working with an innovative events company.

Research example – stroke configuration

Saving lives in Manchester

In 2014, Greater Manchester had been aiming to centralise services further for some time, but change had been delayed. In London, where radical centralisation took place so that all patients were seen in hyperacute stroke units, the mixed-methods evaluation found reductions in mortality and length of stay above and beyond reductions observed elsewhere. In Greater Manchester, where only a selection of patients were seen in hyperacute units, there were no reductions in patient deaths beyond what was observed elsewhere (but shorter hospital stays). Qualitative research published later as part of this study showed how implementation models differed, with simpler, more inclusive referral pathways and a ‘big bang’ launch of changes in London, supported by quality standards (linked with financial incentives) and hands-on facilitation, compared to a more complex and phased approach in Manchester (Fulop et al 2019).

Sharing early findings with clinical leaders, engaged throughout the study, influenced decisions in Manchester to push forward a more complete centralisation of services. Before the results were published in the BMJ (Morris et al 2014) and having discussed with the stroke network, health economist Steve Morris produced an estimate that an additional 50 deaths per year could potentially be prevented by this further reorganisation. Local leaders harnessed this figure to argue against any further delays to implementation.

This figure was central to the publicity campaign, which supported local buy-in for the new system from the public, local authorities, commissioners, and providers in GM. This included an infographic produced by the local network, a briefing and tweets from local provider and commissioner organisations (under the hashtag #gmstroke). Greater Manchester agreed and implemented a fully centralised model in 2015.

Latest published findings by the team show the sustained impact of these changes (Morris et al 2019). In 2015, more than four out of five stroke patients in Manchester were treated in a hyperacute unit, more than double the rate with partial changes five years earlier. The researchers estimated that there were around 69 fewer deaths a year in Manchester, and recent national stroke audit data confirm that stroke services in this area remain among the highest performing in England.

Mobilising research at a time of crisis

More recently, we have seen research teams and the wider system rise to the new challenge of the COVID-19 pandemic. Research has been delivered at pace and findings have been quickly made available to meet urgent demands. This includes an evaluation of new ways of supporting people at home (Box 7.2).

Research example – home oximetry monitoring

Keeping people with COVID-19 safe at home

Teams led by Naomi Fulop in London and Judith Smith in Birmingham carried out a three-month rapid evaluation of home monitoring or virtual wards during the pandemic between July and September 2020. These systems arose to monitor people with COVID-19 who may be getting worse at home, sometimes using pulse oximetry to check oxygen levels, to help them be admitted to hospital at the right time or stay safely at home. This was a new way of working for the service, with models set up in days or weeks rather than months. The team wanted to assess how well these had worked and what could be learned for future shocks or crises. This study consisted of a rapid review of evidence, brief data-collection exercise at eight sites to review staffing models, costs and patient experience and implementation study. From this work, the team established a typology of models which were either primary-led, secondary-led, step-down hospital care or mixed, with particular issues in each category. The implementation study showed how service leadership and collective goodwill supported very rapid change. Problems ranged from unclear referral criteria and pathways to availability of pulse oximeter devices and data challenges, particularly for primary care-led models. Findings from this project were shared with central policymakers in the UK, virtual ward collaboratives and newly formed communities like the NHS home pulse oximetry learning network.

Interview – Naomi Fulop

Speed dating – build on good relationships with stakeholders

I talked to Naomi Fulop, Professor of Health Care Organisation and Management at UCL, who reflected on the rapid nature of this project on home oximetry monitoring during the pandemic. What would she say to other researchers?

‘I have learned that it is possible to carry out work rapidly without compromising standards, when it really matters. It helps to have good relations in place with key stakeholders – you can build new relationships virtually, but that can be difficult. It’s important to grab opportunities as they come. I worked closely with the national clinical advisor on sepsis and deterioration and colleagues, who helped me share findings with existing service networks. In one week, I was able to reach many hundreds of important local decision-makers across the country through sessions at different learning networks and communities of practice. That was partly possible because these events were virtual. But the main enabler was having the relationship with clinical and service influencers and real interest from staff in the work that we were doing.’

Sometimes researchers need to be flexible and respond to a changing context. The present COVID-19 epidemic shows many ways – some creative – in which researchers have accelerated or repurposed their work to serve decision-maker needs (Box 7.3).

Research example – sharing emerging evidence on Long COVID

What do we know about Long COVID?

A group of clinicians, patients and researchers met in the summer of 2020 to consider evidence on the management and services for people living with COVID-19 and experiencing long-term effects. There was little published research at that time, but drawing on the lived experience of existing support groups and practitioners, some particular problems and research needs were identified. This included a growing recognition of the different constellations of fluctuating symptoms which made it difficult to diagnose and to access or plan appropriate services. Given the emergent state of evidence, a dynamic review was judged helpful which could signpost recently commissioned research relevant to those living with COVID-19 and resources from professional bodies and patient groups, as well as identifying questions for future research, recently updated with a second report (NIHR 2020). The report author, Elaine Maxwell, noted: ‘We know a bit more every day about this phenomenon. There is a lot of research just starting, but it will not be ready for some time. Our aim in this report was to use the insights now from speaking to people living with COVID-19 to shape the services that are offered now and the research we need to improve support and care.’ Parts of the review were updated in March 2021 as more evidence became available (NIHR 2021). The report signals the known unknowns and provides a roadmap for future research and service development.

The pandemic has accelerated our need for more dynamic models of research synthesis. But many developments to increase the responsiveness of evidence production and use were already underway. This includes living systematic reviews, defined by Elliott et al (2014) as reviews which are ‘continually updated, incorporating relevant new evidence as it becomes available’. This recognises that updating can be intermittent, teams disbanding or taking too long in stop-start fashion to provide information which decision-makers need at the right time on topics of importance. Indeed, Shojania et al (2007) estimated that almost a quarter of reviews within two years of publication had not taken into account new evidence which would change understanding of the benefits or harms of treatments. Other developments, from use of big data and automated data-mining to crowdsourcing, are driving new expectations of the timelines for finding and synthesising evidence. While much of this debate has been around formal systematic reviews and controlled trials – with parallel debates on living clinical guidelines – this does not just apply to biomedical research. The call for greater efficiency and responsiveness can be seen in all kinds of health and care research.

When is when?

We talk about research having impact or being used, but it is often difficult to measure precisely. What counts as evidence being used? There is now a growing body of knowledge looking at adoption of research into practice with complex and overlapping time lags (see for instance, Hanney et al 2015), but there is still a common assumption of a fixed point where research has traction. Theoretical works like Carl May’s influential normalisation process theory provide a structured way of studying how innovations take hold and become part of mainstream practice (May and Finch 2009). This has spawned a whole branch of theory-led implementation studies including, for example, a timely application of this approach to study the rapid transformation to remote working for office staff under COVID-19 (Carroll and Conboy 2020).

What interests me though is the dissonance between the assumed ‘when’ in many accounts of research promotion and use and the reality. Some time back, the researchers Hutchinson and Huberman (1994) looked at the spread of innovative practice in teaching science and mathematics in schools. They concluded that ‘even when linear models for dissemination were “successful” in getting a product through the classroom door, they were not decisive in firmly rooting the innovation in place’. In order for that to happen, the findings had to resonate with what ‘felt right’ to teachers and school leaders and their lived experience.

In a very different context, DuVal and Shah (2020) looked at decisions about antiretroviral medication regimes by policymakers in different sub-Saharan African countries. Their fascinating analysis showed little congruence between the timing and publication of ‘best’ evidence of clinical effectiveness and uptake into policy and practice. The authors noted that ‘gold-standard scientific evidence played a relatively minor role’ in influencing policy. Much more important was a sense of momentum across the subcontinent towards a particular regimen, how easy it seemed to implement and how well it aligned with existing service models. Again, we can see the complex journey of evidence into decisions, making it difficult to predict and measure time taken to have traction.

In both these examples, the importance of context and ‘readiness’ of the environment is as (or more) important as the quality and relevance of the research itself. Factors include alignment with wider policy – ‘what we need to do’, professional wisdom or values – ‘how we care for people’ – and organisational culture – ‘how we do things here’. These will all affect how and when research will land and make a difference. Although many aspects will be outside the control of individual researchers and research teams, there is much that can be done to maximise your chances to influence policy and practice.

Practical Pointers to when you could have most impact

Know your context

You need to keep abreast of policy and service developments, which may make a difference to the context in which your research lands. That might mean browsing the HSJ, Social Work or Caring Today, or other target ‘trade press’ (see also, social media). Having practitioners and others on your project steering group will also help you to stay relevant and informed. This includes what is important now and scanning the horizon for future developments. Building and maintaining relationships with key service contacts will help you to be able to identify ‘windows of opportunity’ when your research might land.

Little and often

Have a plan for sharing interim and early findings in a responsible way. Research funders now encourage flexible ways of promoting research, as long as agreed quality checks are met. This may include preparing embargoed versions of your work and developing rapid preprint outputs. If there is a window of influence, you may want to consider slidepacks, toolkits and tailored outputs for particular audiences.

Reflect back

Think back on a past project. What do you know now about factors which affected the reception of these findings? What could you have done differently to increase relevance or impact? Could you have anticipated some of the changes in policy or practice at the outset? What sources of intelligence could have helped you pitch this better?

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