Can data analysis help the NHS to be a better ‘people business’?

Stephen Dorrell recently told a Westminster health conference that due to the distinct nature of health care services (‘a people business’), the largest ingredient in improving the NHS is its staff.

He pointed to the fact that, while improvements have been delivered in other sectors through the use of technology (the classic example being the automotive industry), this isn’t possible in the same way in the NHS. He was speaking in terms of productivity gains, but I believe the same can be said for quality improvements. Machines and technology can’t provide the compassionate, high quality care that patients desire.

Here at the Health Foundation, we have long focused on the capability of people through our Improvement Science Fellowships, Generation Q cohorts, Clinical Scientist Fellowships and recently through the Q initiative.

Technology, and data more specifically, could also be vital in allowing innovation to flourish across the NHS at a local level, if frontline teams were able to use it to develop tools and insights to improve patient care.

This is why our current funding opportunity, Innovating for Improvement, is particularly interested in applications from teams whose projects will apply an innovative use of data. This could be new uses of existing data, innovative ways to analyse and visualise data, or novel new sources of data. We have £1.5 million of funding available, so that up to 20 teams can receive up to £75,000 to test and develop innovative ideas. (If you’re interested, the programme is open for applications, and the deadline to apply is midday on Tuesday 28 March 2017.)

One of our current Innovating for Improvement grant holders, based at Valentine Health general practice in London, is aiming to personalise care for patient subgroups at the practice. Staff at Valentine Health noticed that they had some persistent high users of the practice, so they aimed to co-design (with patients and staff) and implement ways of delivering care tailored to these patients, with the overall aim of improving outcomes for these patients and reducing their reliance on secondary care. Although there are national plans to reduce overall use of secondary care by high-risk patients, Valentine Health wanted to use their data to identify and manage high-risk individuals to attain better clinical outcomes, and make their own general practice more sustainable and efficient for patients and staff.

There are a high number of characteristics that affect how much a patient uses general practice, meaning they have diverse needs. In this case, the Health Foundation’s in-house data analytics team were able to work with Valentine Health to identify patient groups who could benefit most from an intervention.

Using data analysis, we found that being older and having more long-term conditions were patient characteristics associated with high usage of general practice care. We found other intriguing patterns in the data.

For instance, even after taking into account patient characteristics such as age and diagnosed long-term conditions:

• Those who lived alone were more likely to be a high user of primary care than those who lived with other people
• For those who lived with others, if a patient lived with a high user of primary care, they seemed to be more likely to be a high user themselves
• Older patients were more likely to be high users of pre-booked appointments, but not walk-in appointments

The doctors at Valentine Health are now using insights from the data analysis to co-design interventions to improve the care delivered to older people and those with long-term conditions. These will be tailored to the particular needs of patients and are still in development. However, some recent innovations include offering patients with long-term conditions enhanced continuity of care with their named GP; in-depth reviews focused on setting health improvement goals, and referral to local community services and resources. The practice is also looking into developing group appointments focused on managing chronic pain. Further, the practice has created a designated afternoon session for older patients, who had reported it being stressful sitting in the Walk in Clinic waiting room with lots of children running around.

In the end, the NHS is a people business, but we’ve found that data driven quality improvement is aided by collaboration between frontline staff and those analysing data. Allowing clinicians and NHS staff to get useful feedback from data, while they work, will help them to deliver care in a way that works for their patients.

Isaac Barker is a Data Analyst at the Health Foundation