An unlikely data pioneer: four lessons for today’s data analysts from Florence Nightingale

The new Florence Nightingale Award for Excellence in Healthcare Data Analytics recognises data analytics practitioners who have gone the extra mile in delivering innovative improvements for the health care system. This blog looks at what lessons today’s analysts can learn from Nightingale’s pioneering work, and considers what she might think of today’s health data landscape.

You know the dreaded ice-breaker question where you’re asked to reveal a ‘fun fact’ about yourself? Well, my go-to answer is that I’m distantly related to Florence Nightingale. She was my great, great, great, great aunt on my mum’s side.

I’ve always felt quite proud of this association. After all, she is considered the founder of modern nursing and became a national icon for her actions to revolutionise hospital management during and after the Crimean War. To mark the bicentenary of her birth the World Health Assembly has designated 2020 the International Year of the Nurse and the Midwife.

But recently I discovered a less known side to her. One that makes me feel a more personal connection to her given my career as a data scientist analysing NHS data. Nightingale was a passionate statistician and data visualisation pioneer. In fact, she coined the term ‘applied statistics’ and went on to become the first female member of the Royal Statistical Society in 1858. The more I learn about her, the more I see that she is a role model for modern practitioners of statistics. She’s known as the ‘lady with the lamp’, but maybe we should call her the lady with the data, because she was at least as illuminating in the world of statistics.

That’s why the Health Foundation and Royal Statistical Society have joined together this year to launch the Florence Nightingale Award for Excellence in Healthcare Data Analytics. The award celebrates the work of UK data analysts who have informed improvements in patient care.

So, what are the lessons from Nightingale’s life for today’s data scientists?

1.    Choose to tackle the problems that matter most 

Snubbing Victorian convention to follow what she believed was her calling, Nightingale didn’t shy away from tackling the worst of society's problems. During her long career she shed light on a huge range of issues including hospital mortality, child labour, hunger relief, work houses, prostitution and crime. She used data to tackle real world problems and help to save lives. If she were alive now, I think she would challenge us to do the same.

At the Foundation, our new Data Analytics strategy focuses on ensuring that everyone’s health benefits from analytics and data-driven technology. We also think it’s vital that new developments in analytics have a positive impact on reducing health inequalities. This means ensuring that new technology is developed together with underserved communities and meets their needs. It also means considering how we can direct investment in data and technology so that it benefits deprived and marginalised communities.

2.    Involve yourself passionately in the process of gathering data 

Nightingale collected data about everything. She thought that, ‘To understand God's thoughts we must study statistics, for these are the measure of his purpose.’ A friend said: ‘However exhausted Florence might be, the sight of long columns of figures was perfectly reviving to her.'

After the Crimean War, she became obsessed with data quality and standardisation. She coordinated multi-year data collection efforts across the world. Using data and novel statistical methods, she showed what could be achieved by following the evidence.

In the age of ‘big data’, direct involvement in data collection might not be possible, but there are plenty of techniques today’s analysts can use to ensure their results are robust. We need to take time to understand the potential biases and limitations of our data sources, undertake careful data quality assessments and incorporate diverse datasets in our analysis.

If she had lived to see the digital age, Nightingale might be delighted by the potential for data-driven technology to improve people’s lives on a massive scale, but she also understood that well-intentioned reforms can have unintentionally harmful consequences and would perhaps urge caution. Plenty of examples show how biased algorithmic decision-making can exacerbate existing structural inequalities and mean that services are withheld unfairly from those most in need. For example, a recent study revealed that an algorithm widely used in US hospitals to allocate health care to patients was less likely to refer black people than white with the same level of need for extra care.

3.    Data on their own are not enough 

Nightingale understood that statistics are political and believed that we have a duty to use their power for good. She was a prime innovator in using statistical evidence, forcefully communicated, as a basis for public policy. Although largely confined to her room for over half a century, she worked tirelessly behind the scenes coordinating campaigns, and made it impossible for MPs and civil servants to ignore her causes.

She also found imaginative and easily-digestible ways of presenting her data and always had a careful communications strategy. She invented a new type of chart to show that in-hospital mortality was largely preventable with simple sanitary reforms: a comparative polar-area diagram, known today as the Nightingale rose. She delivered these to influential people, and told them to hang them in their offices. If alive today she might love the vast reach attainable through social media and the possibility of sharing code and other analytical resources through sites like Github, as my team has recently done. 

4.    Collaborate for greater impact 

Nightingale had many collaborators throughout her career. She befriended the health reformer and statistician William Farr and they worked together on an array of statistical design innovations. Later, she joined forces with Karl Pearson to lobby for university teaching on applied statistics. In 1911, a year after her death, the Department of Applied Statistics at University College London was founded.

Successful collaboration and partnership working are no less important to achieving impact in today’s health analytics landscape than they were in Nightingale’s time. At the Foundation we know that by working with others, we can have a much bigger impact on tackling the issues affecting the nation’s health, while helping to reduce the fragmentation that currently exists in the system. We have already established two collaborative analytics units (the Improvement Analytics Unit and the Networked Data Lab) and expect to announce new significant partnerships in the coming year.

We need to continue Nightingale’s legacy by calling for further investment in analytics if we are to really unlock the potential of the growing mountain of NHS data to benefit patients. Our Advancing Applied Analytics programme has provided seed funding for 33 projects in front line organisations across the UK. We have also been growing communities of analysts by supporting initiatives like the NHS R Community and the Association of Professional Health care Analysts.

Nightingale devoted her life to using statistics for good. Her work made a huge impact and laid the groundwork for things we now take for granted, like being able to compare hospital’s performance. Now it’s up to us to continue her legacy.

We need to recognise good practice. If you know a team or individual that deserves recognition for their work to deliver innovative improvements for patients, nominate them for the Florence Nightingale Award for Excellence in Healthcare Data Analytics by 28 February 2020.

Hannah Knight (@HannahEllin) is Principal Data Analyst at the Health Foundation.