By David Henderson, staff and alumni of Edinburgh Napier University 

Having just completed his PhD a David Henderson reflects on his time as a student nurse and what brought him to his current role as a research fellow at Edinburgh Napier University. Davids dream for nursing is better access to research opportunities for nurses.  In his current role David is using big data to make lives better and gives insights into the research he is now doing to make that happen.   

I *hated* research papers when I was doing my nursing training. Let’s face it – they are hard to read but you *had* to cite them if you wanted to pass. If you’d said to me that within 10 years of finishing nursing training, I would have a PhD and be doing quantitative research then I would have laughed in your face. I think that is a common experience for many nursing students. Most of us went into nursing because we like interacting with people and can tangibly see the difference we make in their lives. Despite all the advanced skills (which I loved learning), I still say the most rewarding experience of nursing was personal care. Helping someone who can’t wash and dress themselves is a very special privilege and crosses a barrier that is inconceivable in any other walk-of-life. Seeing someone look visibly better after such a “basic” intervention can be heart-warming. So how do you jump from there to big data analysis and statistics? By asking questions. Why is that person getting re-admitted? Why did that person take longer to respond to treatment? What could change at home to help this person stay out of hospital? How can we reorganise this system to make it better for patients and staff? Why do people from poorer areas have worse outcomes??

Nurses questioning how to enhance their practice and improve the health of their communities

Then you start to read a bit. Then that makes you ask more questions. Then you are hooked. Clever answers aren’t just for the doctors. Nurses have a unique insight into what works for patients and, for my type of research, how the health service works. A lot of data analysis is about knowing what the numbers mean. Understanding the BNF is a huge advantage for a lot of administrative data research because the Prescribing Information System (PIS) is one of the best resources world-wide for matching treatments to outcomes. Researchers with non-clinical backgrounds must get their head round this weird encyclopedia that nurses use routinely every day. Furthermore, those that work in unscheduled care know what a Key Information Summary (KIS) is, how it is used, and what it can and, more importantly, can’t tell you. Even knowing the care pathways in out-of-hours care is a huge advantage over those that have no experience of working in the NHS. Things that we take for granted are specialist knowledge. My own research involves looking at interactions between health and social care services. It is intuitive that many people use both services and that access to one service has implications for the other. However, we have very little evidence that this is the case. That’s because, until recently, we haven’t had access to data that would let us look at this. Now we do, and people who understand how people move in and out of these services are well placed to make sense of the numbers that may seem confusing to others.

Now I’m not saying that everything is easy, nor that stats and data are for everybody but there are many nurses out there that have loads to offer in academia. These blogs are named after Florence Nightingale who was one of the first people to use data analysis and visualisation to show that changes in care delivery can save lives. This application of research to augment her clinical work marked her as a true visionary and leader. I would encourage every nurse to constantly ask questions – and don’t stop until you are satisfied you have the right answers. Those questions will drive you to learn the skills that will help you answer them – and follow in the footsteps of the most famous nurse of all. 

Leave a Reply

Your email address will not be published. Required fields are marked *