Medicine is a wide interdisciplinary area in which multiple fields of knowledge converge, such as mathematics, physics, biology, engineering, and others. This convergence had produced an explosion of technological developments and knowledge for new treatments and diagnostic strategies. Thus, this rich knowledge team has made it possible for humanity to better understand your body, mind, and health. At the center of this revolution had been the data sciences that had transformed how medicine is understood, how physicians make decisions, and how healthcare is delivered. Most of this work has been carried out by engineers, mathematics, and statistics, however, fundamentals of the medical context can be simplified or omitted by people without training in health science. Additionally, physicians must be directly involved in the analysis of medical information to improve interpretability and interoperability.

A recent case study carried out at the University of Edinburgh, UK showed that physicians during their training program should receive training in data science and statistics. A course in data science was included for year 2 undergraduate medical students in 2018. Approximately 210 students received the training annually since that moment. The course aims are to equip students with the key foundations and data skills for the data-intensive medicine of the future. No prior data science, programming, and statistic experience were required. Three important core themes were emphasized in this case study: statistical analysis of biomedical data, relational databases for medicine and healthcare, medical ontologies, and graph data representation. Practical tutorials and computer labs also were considered during this course. Programming labs on analyzing data used of R and RStudio. Finally, synthetic but realistic clinical datasets were provided to students during practical sessions [1].

Results of this disruptive research study showed that students who received data science training during their medical school have been better prepared for data-driven projects in health sciences. Also, students have been better equipped for the interactions that require a basic understanding of data science, such as psychology, epidemiology, as well as mathematics, computers and medicine, or even medical physics and biomedical engineering. Even if, for many students at the beginning of the course, data science was outside their interests or seems to be not useful in their future studies and career, these thoughts seem to have changed after the use of clinically relevant datasets for experimentation or the use of the relevant clinical case to discuss.

Undoubtedly, the future will require learning changes and medical schools are getting it. The physician with a data science background will allow confronting more easily complex and interdisciplinary problems in the context of health science. Now, the challenge is making this possible. What do you think, should these kinds of courses be included or not in the training of new doctors in medical school?

Source:

[1] Dimitrios Doudesis, Areti Manataki, Data science in undergraduate medicine: Course overview and student perspectives, International Journal of Medical Informatics, Volume 159, 2022