Why health data science research needs a makeover
- Roshni Joshi -
We’re bombarded with daily headlines bellowing the strain upon our beloved NHS. With over-worked and exhausted frontline staff, ever-increasing health inequalities, and an ageing population with multiple comorbidities, I think now more than ever is the time to pay attention to data science and exciting technologies. The correct application of rich healthcare data and new and emerging healthcare technology can help to predict disease, determine the efficacy of new interventions and identify people who might be at a higher risk of certain diseases. But, like lots of people from “traditional” healthcare backgrounds, training to be a data scientist seems daunting, even if it is the future of the field.
My journey into data science began during my Master’s degree when I started to comprehend the utility of data science. I was using primary care data from the Clinical Practice Research Datalink (CPRD) to investigate associations between lipid-lowering drugs and mortality following a respiratory illness. I rapidly had to learn about data cleaning and management and there was A LOT of cleaning needed! This research, in combination with my subsequent job working at the National Institute of Health and Care Excellence (NICE) geared me up to undertake a PhD at the intersection of data science and health. But starting out in data science, and surviving in the academic culture, especially as a woman, is not without its challenges. One HealthTech regularly receives requests for help about breaking into data science and how to crack in in academia – so here are my thoughts!
Starting a PhD and diving into programming and data science was daunting, especially as I would have to learn new methods. I knew that I would have to learn to code efficiently and effectively and ultimately apply this to my data in order to produce some coherent and valid research, with the hope that it would make a difference to someone, somewhere! My PhD aims to clarify the role of triglycerides (a type of fat) in cardiovascular disease (atherosclerosis, coronary heart disease and stroke) using a range of Big Data methods. I’m going to be using lots of different data – all of which I’ll need to fit together before I even begin to answer my research aims! I’m all for innovative technology, but learning new skills can be overwhelming, especially when colleagues and peers appear to be much better informed than you. Data science is still relatively new and therefore the field is full of people like me – somewhat of a novice attempting to learn and build new skills. There are so many resources available, from courses and tutorials available online to face-to-face teaching through the university, and quite often most problems can be solved by simply asking our dear friend Google, only to find that many others have encountered similar programming hurdles. Appreciating this and asking for help when I need it has be invaluable, particularly as PhDs require immense perseverance with quite a steep learning curve at the beginning.
My personal experience has been of an academic environment that is supportive and encouraging and thus far entirely positive. I’m a strong advocate of women in STEM positions and despite the growing demand for talented individuals, women are still underrepresented. I enjoy working in an academic environment, alongside other passionate people who really care about their work and research. I’ve been fortunate to be surrounded by colleagues from very diverse backgrounds, and certainly, there is a strong need for people of all shapes and sizes to be introduced and accepted into academia, data science and technology. I do believe though, it’s important to change the stereotypical face of scientists or academics. Gone are the days of thinking that a scientist is a mad professor, stuck in a lab for all hours, working on an experiment. This can perhaps suggest that academia is represented by one type of person – usually a man, usually white, and it’s about time we break this stereotype to encourage young girls into STEM careers and keep them there.
Doing a PhD is hard work with many challenges and bumps in the road along the way. It is just the beginning of your career – a time to figure out who you are and where your interests lie. Data science and health technology is an exciting, progressive field and requires diverse and talented individuals at every level, no matter your experience and background. So, whether it’s encouraging school children, your colleague or neighbour, writing a blog post or speaking at conferences, we can all make data science and health technology interesting and represent a new wave of people who know who they are and what they can bring to the table! It’s also time to change the view of female academics and make it okay and acceptable to be interested in make-up, nice clothes, the latest shoe trend AND be a respected and capable researcher and scientist. I happen to love shoes and fashion, but I also think it’s cool to discuss an arbitrary P value of 0.05. Reading the latest edition of Vogue and wondering how you’ll style your hair over the weekend whilst simultaneously writing awesome algorithms is just another flavour of modern health data scientists. Having other interests aside from science and research, painting your nails in the office or wondering if you should wear red lipstick to work doesn’t detract from intellect or ability.
My point is, you, I, women and people in general, don’t need to ascribe to a pre-set mould or idea, and that we can change the way data scientists and academics are perceived. Healthcare is in a revolution, and all the women working in health care are part of it. However, for the time being, perhaps we have to work a little harder to prove that it’s possible to have a brain and be feminine in any sense of the word if that’s what you feel like. And if not, that’s OK too. But even more so, it’s about finding the courage and confidence to be yourself and having faith in your abilities. Everyone is unique and different and it’s important to me to find a way to let those individualities shine and also be taken seriously.
Roshni is a BHF PhD researcher at the Institute of Cardiovascular Sciences at UCL, with a background in Biomedical Science and Public Health and Epidemiology
Do pop Roshni a line if you have any comments, thoughts or responses! She can be reached on: