Making learning practical for health and care innovators
Learning is core to innovation – but when health and care innovators are working at pace, with multiple demands on their time, this can easily fall by the wayside.
In this context, it’s vital that all learning is applied, practical, and relevant. At Social Finance, we’ve identified the key principles to allow us to help innovators learn pragmatically.
Our work as a learning and support partner for innovation programmes
One of our Data + Digital Labs team’s core goals is to spark, enable, and accelerate data and digital innovation within the health and social care system. Over the last two years, we’ve used our Routes to Scale framework to support two major innovation funding programmes that aim to catalyse new approaches to health and care.
We’ve partnered with the Wellcome Trust as the design and delivery partner for their Data Prize in Mental Health, which supports 11 multidisciplinary teams to research anxiety and depression in young people, and develop a digital tool that supports the mental health research community. The three prize-winning projects were recently announced.
We’re also a support partner for the Health Foundation’s Tech for Better Care programme, which supports 10 teams of health and care providers to innovate new models of care which are tech-enabled, relational, and proactive.
In both programmes, our role is to help innovators think differently. Combining cohort training, 1:1 coaching, and dedicated resources, we aim to inspire new methods and approaches that can unlock impact at scale.
Across both programmes, pace requires pragmatism
Data and digital innovation’s ‘fail fast’ mantra can make programmes feel fast-paced. This can pose challenges for innovators. Longer-term learning, while vital, is often deprioritised in favour of pressing project work and immediate actions.
We sympathise with this: we also want innovators to focus on developing ideas and building solutions. Even the most useful and well-intentioned learning activities take people away from their individual projects, so it’s paramount to find balance and ensure that learning is as targeted and relevant as possible.
We’ve found that three simple principles allow us to maximise relevant, practical learning:
1. Plan learning that can be put into practice immediately
To help innovators action useful learning straightaway, balancing theory with real world examples is most effective. Theory provides principles that can be adapted flexibly to suit each innovator’s context; examples show how this has been achieved successfully in the past.
For the Data Prize, we offered teams an early workshop on involving lived experience of mental health problems in research, beginning with some overarching theory on co-design and best practice on the ethics and politics of bringing wider voices to the table without tokenising them. Our high-level thoughts are collected in this blog.
When the teams requested more concrete examples of embedding lived experience, we prepared case studies on topics ranging from communications (making academic language more accessible) to prototyping (directly testing tools with young people).
We’ve also found it helpful to provide workbooks, templates, and resources for teams to take away. This saves innovators from having to reinvent the wheel in designing methods and outputs.
2. Help innovators prioritise: what’s core, and what’s extra?
Innovators will always have competing priorities. Tech for Better Care teams, in their explorative research phase, could have spoken to innumerable beneficiaries, informal carers, clinicians, social workers, tech providers, and beyond. Our role as a support partner is to help teams prioritise: what is important now, and what can be backlogged for another day?
We did this by helping innovators apply agile methodology, despite their lack of familiarity with this approach:
- Working in two-week sprints in which they test, learn, and iterate – so that the focus is always on what is most useful right now.
- Writing ‘Research is done when…’ statements – so that teams recognised when they had achieved good enough insights to stop researching, rather than scheduling further interviews for diminishing returns.
3. Do whatever teams need us to do – even if it’s less obvious
Often, the learning that teams need is not dedicated design, digital or data knowledge – it’s help navigating less obvious obstacles, from tricky procurement processes to recruitment challenges.
This month, we interviewed the three winning Data Prize teams about the support they need to achieve impact at scale. Some of their requests were technical – can we find a way to safely analyse sensitive mental health data with an online tool? – but others were broader. How do we tell our story? How do we deal with team turnover? How can we sustainably finance our idea?
We embrace and encourage this wider focus: our ethos is to be impact-driven, not activity-driven. We’re agnostic about the knowledge we pass on, as long as it meets the most pressing needs.
Being agnostic about knowledge is easier said than done. It requires a blend of expertise which is typically siloed in separate organisations and teams: digital vs. health, strategy vs. operations, finance vs. frontline experience. Collaboration and partnerships, within Social Finance and beyond, are of crucial importance. To help the Data Prize teams, we’re bringing in diverse experts from across our organisation and outside to bear on these problems, offering masterclasses in building open-source communities, sustainable resourcing, and innovative finance.
In doing so, we try to model the multidisciplinary approach we want to support in our innovators.
Interested in our approach?
You can read about the Wellcome Data Prize winners, and the Tech for Better Care teams, to learn about their innovative work.
See our previous blogs on how to overcome systemic constraints to using communities of practice, and how to be an effective learning and support partner.
If you’re interested in hearing more about Social Finance’s support offer for innovation programmes, we would love to hear from you. Please email michael.crowder@socialfinance.org.uk to learn more.
