Let’s think for a moment about optimism. It can undoubtedly be positive, providing resilience in the face of setbacks, a promise of something better when times are hard. But have too much, and obstacles start to get ignored, unjustified risks taken, and what you were so optimistic about in the first place doesn’t come to pass.

There is nowhere higher in the health care optimism stakes right now than the NHS England programme of Vanguards. There’s good reason behind the optimism - a range of highly motivated individuals across 37 areas trying to lead change to improve the lives of their populations. After spending time with the initial Vanguard cohort at their launch event in March, the sense of positivity and enthusiasm was palpable.

But how do you stop optimism getting out of hand? In his book Thinking Fast and Slow, the Nobel prize winning psychologist Daniel Kahneman talks about an exercise called the ‘premortem’ (with thanks to Tim Gardner for the tip-off). Simply put, you imagine a time in the future when the plan you are looking to implement has been a complete disaster, and ask yourself why it happened. The virtue, Kahneman writes, is that 'it legitimises doubts… it encourages even supporters of the decision to search for possible threats that they had not considered earlier.' It’s the effect of putting a punctured bike tyre in a bucket of water to find where the hole is.

We ran a premortem with a range of Health Foundation colleagues to talk about the development of new models of care, such as those led by the Vanguards. Asked to think about a date in 2018 when ‘new models of care’ had become a term of disdain due to their abject failure, discussion brought out three main themes as to why it might have happened:

The unpredictable

Macmillan’s aphorism that 'events, dear boy, events' are most likely to blow governments off course is equally well applied to health care. Individually, it’s unlikely that in the next three years there will be an Ebola outbreak in the UK, a scandal the size of Mid-Staffs, or an acceleration of antibiotic resistance - but it’s highly likely something major and unexpected will. The task is not to plan for the specific, but how you build in just enough steel in your plans to have them withstand sudden shocks, while still retaining flexibility to adapt to new circumstances.

The entirely predictable

As you may expect from an organisation focused on the process of improvement in health care, Health Foundation colleagues highlighted a number of change-management risks which many of us are incredibly familiar with. The changes being made aren’t well communicated. Staff don’t have the time and headspace to plan changes, and disengage. The fundamental nature of context (as highlighted in our recent report) is overlooked. Not enough money was put behind it, or cuts elsewhere led to it being impossible to implement. Change focuses on structures rather than care delivery. Workforce implications weren’t thought through. Too much time is spent talking, not doing. Such factors are wearingly familiar because they are mistakes made again and again. If the Vanguards are to systematically avoid them, they would be setting a (wholly welcome) precedent.

The data

Our scenario was deliberately based on the premise being that the new models had failed. Of course, after three years we’re unlikely to know whether such major changes will have done so or not. This could be because changes hadn’t had time to see effects, or that measurement systems weren’t tracking the right outcomes, or hadn’t been put in place at all. These are all concerns which could have been placed in the ‘predictable’ box - but are worthy of a special mention due to the nature of the new models. This is partly because expectations of them are so great that any scrap of data is likely to be seized upon to inform snap judgement rather than waiting to see the whole picture. But also because the development of new models are experiments which are likely to go wrong and learn and change and go wrong again, and all in a perfectly healthy way. Without good data - both qualitative and quantitative - such iterative learning will be impossible.

The history of national pilots to deliver integrated care (whether they be Demonstrators, Pioneers, or Testbeds) is not a happy one. However, forewarned is forearmed. Perhaps those developing new models of care should start talking about what their biggest risks are: and then advocating at all levels for change to mitigate them. What would your biggest fear for new models of care be?

Richard is Director of Policy at the Health Foundation. This blog was co-authored by Felicity Dorman, Senior Policy Fellow at the Health Foundation.

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