Probably most of us think we are doing a good job. We have the right experience, attitudes, values, knowledge, character. We go to work every day. We make progress. We do good.

Or so we think. But how much of this is comfortable illusion?

A few years ago the Health Foundation funded a study which analysed the perceptions of boards of hospitals in the US and the UK. What did they think the quality of care was like in their hospitals? This was compared with some accepted measures of quality. The result? The boards of poorly performing hospitals had almost the same perceptions of those in the best performing – that quality was good.

My bet is that the same result would be found if you had asked the staff and, dare I say it, many of the patients. And the more pressure applied to improve care, probably the more blindness will result.

Sure, the quality of care can’t be reduced to a few simple metrics. But they can help show up variation and lack of progress that are at best inconvenient.

Which is why using data and measurement is central to improving quality – from the ‘national’ health system level to the local, to the personal.

On the national: this month, along with the Nuffield Trust, we published analysis showing trends in the performance of the NHS across the four countries of the UK (also see our interview with Professor Nicholas Mays, one of the report authors). Overall, on the 15 or so indicators examined, there is improvement in almost all. There is no dent in the trend line between the four countries showing when devolution happened. So whatever the policy cocktail applying to the NHS across the four nations, none seems to be outperforming another, despite the heated political differences about the use or not of competition and choice.

The exception, suggested by a worsening in waiting times in Wales since 2010, may be down to weaker performance management against the waiting target, a cut in funding, and possibly the reorganisation of providers in Wales – all political choices.

The bigger message suggests a wider set of forces are acting on health systems that influence performance, unrelated to those crafted by politicians, that are mediated locally.

So, on the local: how can teams trying to improve care measure progress when the intervention they are trialling is complex and changing, and not as simple as a fully formed pill? Tom Woodcock, a Health Foundation Improvement Science Fellow, has blogged his twelve tips for how improvement teams might up their game on measurement. In particular try using statistical process control charts (don’t be put off by the name) – simple and visually appealing, tried and tested.

If you want to be ahead of the curve in measuring safety, try moving from measuring past harms to include a more comprehensive assessment of current risk. The Foundation has just published a practical guide on this and later this year will be giving grants to centres which can trial this new approach.

And, lastly, on the personal: how to begin thinking about measuring how person-centred care is – what matters to the individual – is the focus of Dr Alf Collins’ contribution this month. Many of us have been brought up to be more sceptical of the n=1 study, preferring aggregate data, but our scepticism could just as easily be the other way around.

Finally, measurement is dry and often farmed out to academics or analysts on the logical rational end of the spectrum. But it should be pulled back centre stage to be owned by those more used to doing, caring and probably those who are least numerate. Only then perhaps we can pierce the comfort we’ve grown used to.

Jennifer is Chief Executive of the Health Foundation, www.twitter.com/JenniferTHF

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