by Josh Szymanis
As a fourth-year medical student, health economics is a topic that has been mentioned numerous times, but I would not consider myself to have been particularly well exposed to it. I understood the importance of it and how it is used, but nothing about how the information and data is generated.
The first half of my fourth year consisted of lecture-based teaching, and the second of Student Selected Components (SSCs) – six-week placements in fields largely of my choosing. After two clinical placements, I decided I wanted to branch out and experience something wholly different to my peers. However, I had no idea in mind of what that might look like. This led me to an SSC described as “health services research” which I thought sounded both suitably diverse compared to previous SSCs and non-necessitating of ward rounds.
On speaking with my supervisor, the topic of health economics came up. It interested me as it may have an impact on every clinical decision I will make in the future, whether obvious or not. I began my placement with the health economics team at the Institute of Health and Society; the staff in the department were kind enough to accommodate and support me with projects to complete and skill development. Having no prior experience to draw on, the placement inevitably started with a small pile of textbooks to skim through in order to familiarise myself with the health economic concepts and methods I would be engaging with during the placement. Google also proved to be a valuable resource!
My first project was to complete a Health Economics Analysis Plan (HEAP) for a current clinical trial. Whilst this was an unfamiliar undertaking, I had plenty of previous plans to refer to for guidance. Being refreshed on the concepts of Quality Adjusted Life Years (QALYs), Incremental Cost-Effectiveness Ratios (ICERs) and the NICE thresholds for recommending treatments has been an invaluable part of my learning. This also gave me the opportunity to develop my skills in reading papers quickly and picking out relevant sections.
The second project involved statistical analysis, using the program SPSS. It was something I had never used before, and early on I pined for a return to Excel, in a process probably not too dissimilar to the well-known “5 stages of grief”. Nevertheless, by the end of my first week tackling SPSS I was able to produce some usable data. Statistical analysis is the skill I believe will be most useful to me as I plan to be involved in publishing papers in the future.
Overall this placement has been a very worthwhile experience, one that I hope will pay dividends over the course of my career.