Thought Leadership

The lockdown narrative unravels: what future for integrated care?


As the Deputy Prime Minister announces ‘a package of measures to ensure the public receives the best possible care this winter and next’ (DH website), it’s worth asking what happened last winter and the one before.

In the wake of the government’s announcements, and as integrated care systems (ICSs) inherit the delivery mantle, we have missed an opportunity to find better solutions. We were too reactionary, we relied on too narrow an expertise base, and we lost sight of the wider picture.

So, what happened? The initial narrative was that we played a poor hand rather well. Some politicians complained about groupthink and then economists questioned the benefits of lockdown. Recently Lord Sumption went further: “Ministers and scientists responsible for a policy that has inflicted untold misery on an entire population naturally find it hard to admit they may have been mistaken… The official narrative is beginning to unravel.”

While attention has focused on the politics, what of the guidance? In three articles written under the fog of crisis, I made observations that matter less for placing blame (we’ll blame whom we want to, anyway) and more for the future. The fears and guesses that drove lockdown will skew our chances of making ICSs work unless we can look away from politics and generate better guidance.

In Coronavirus and the model (Mar 19, 2020), I hoped that advice might be based on models that optimised the mix of testing, tracking and even vaccination and that priced the options. I noted that UK policymakers had a poor track record with this type of model, and so it turned out. We have some of the best modellers in the world across our campuses, yet only a minute fraction of this resource was funnelled into the logistics of outpacing the virus nationally or building a balanced strategy. Today, the ICS challenge of care for all at unprecedented scale and responsiveness will require new mixes of behaviour, drugs and technology.

In Coronavirus: what’s up with our experts? (ICJ, Aug 2020), I noted the dangers of appealing to but a single type of expert and called for wider pools of expertise before we threw our supply chains overboard and trashed our schools to keep the ship of state afloat. It didn’t seem like rocket science at the time, so it is surprising that it has taken nearly two years to challenge openly the full devastation connected with such a policy. In a similar way, ICSs can only work by building wide collaborations if people are to thrive after episodes of care or avoid such episodes altogether.

In Algorithms of destruction? (ICJ, Nov 2020), I contrasted two worlds driven by algorithms: home shopping that grew vibrantly and education and health that struggled. Simple examples explored how the findings of models require interpretation before we act. The comparison with today’s ICSs is obvious: we’ll need great algorithms wisely applied to deliver.

Data quality was a continual bugbear: the NHS is an excellent emergency service and is developing as a promoter and supporter of lifelong health. However, it is ill-equipped to provide real-time data in a worldwide crisis against a constantly evolving adversary. So, where does good data come from?

Modelling options is our only choice when the future is unutterably new and unbearably complicated. Even an all-embracing programme of research could never have worked. It needed a more agile and creative approach. One strategy lay in creative gaming between teams of modellers generating solutions with their predictions while others countered or triangulated evidence from measurements. Instead, a lot of local data was wasted.

The pandemic was an opportunity to put simulation to hugely effective use. Never before had we possessed such tools or so diverse a set of skills. Balancing epidemiological predictions against employment needs and the economic good of the nation – not to mention treatment against prevention – while designing new mechanisms for care delivery, was never going to be easy but it was possible at last and at scale.

Early evidence that models repay us handsomely started to emerge under lockdown (see this HSJ article or this academic paper). The problems facing ICSs bear similarities to those that drove lockdown – urgency, risk of meltdown, complexity – while the increased backlogs and blockages still put the poorest and oldest most at risk. Worse still, we are broke.

Very, very recently, in a university near, near at hand, someone has modelled what you need to square the circle with effective blends of expertise and predictive models for a better service that won’t unravel this winter or next.