Pursuing a Passion in Medical Research

I have always been interested in biostatics and data analysis of observational research. To me, this is where I begin to truly understand the underlying natural laws and transition from medical phenomenology to science.

My interest was amplified by observing new developments in machine learning and artificial intelligence (AI). I wanted to make use of these advanced technologies to process complex healthcare data into strong data products, such as predictive models.

I started on the part-time Masters of Technology programme at NUS, attending classes on the weekends while I was serving National Service (NS) then. It was during this period of time when I realised that working on large datasets required additional computing skills in data manipulation. Therefore, out of sheer necessity and interest, I started to pick up coding as well.

It was certainly not easy having to juggle this 'extracurricular activity', studies, work and personal commitments at the same time. To return to clinical work right after my NS would have made it difficult for me to attend my classes regularly. This prompted me to take a year off from Residency to fully concentrate on pursuing my interest in Research.

I did have my reservations about taking a year off from Residency to develop my interest in research, as I was afraid that I would end up falling behind my peers and in the worst case scenario, exit Residency. Fortunately, my worries were completely unfounded as my Programme Director (PD) and Faculty were supportive in my research endeavours, especially my Residency mentor - Prof Tan Chee Kiat, with whom I corresponded frequently about the possibility of applying the computing techniques learnt to medicine. 

I was also interested in gaining exposure to the real-world data analytics, but wasn’t sure if I would have the opportunity to do so. Thankfully, the Singapore General Hospital’s (SGH) Medical Board offered me a part-time role at its Health Service Research Unit (HSRU) to do data analytics, while completing my Masters programme.

Up-skilling in computer programming, especially after years of not doing math and statistics was exceptionally tough as I had to put in extra time and effort to make up for it. Nevertheless, it helped that these are my areas of interest and passion, which have steered me to stay the course. Knowing how to prioritise and allocate my time well helps too!

Apart from taking a year off from Residency to pursue my studies in a different field, the experience of doing data analytics at HSRU – a job that is different from clinical medicine – has also taught me the importance of broadening my perspectives. If I were just a clinician, I would probably never have understood the difficulties that analysts face in working with us. But after taking on the role of the data analyst at HSRU, I can understand the frustrations that data analysts experience in collaborating with clinicians. This has inspired me to hone my skills in medical research, in hopes of bridging the gap between clinicians and data analysts in the future.

There is always a challenge in translating routine unstructured operational data into research data and applying them in our daily operations. This usually results in a lengthy data extraction process, which adds on to the frustrations of clinicians and data analysts. Hence, I hope to improve on the data governance and usage processes, so as to add value and convenience to the way clinicians handle and utilise patients’ data. My aim is to develop a continuous delivery pipeline from patient data to clinical monitoring and prediction – all done in a reliable and secured manner.