Starting any PhD can be a bit of a daunting experience. Even more so when you jump into a major international project like EHDEN. Many of the advantages of the project, such as the opportunities for collaboration, its inter-disciplinary nature, and ambitious goals contribute to a high-paced environment, which, as a fledgling researcher, can be a little intimidating. Fortunately, my first experiences with the project left me with an overwhelming sense of collaboration, and that people were really motivated to work and learn together.
A major first challenge was to understand the language that everyone is talking. In a multi-disciplinary project, there is a lot of jargon, and unhelpfully, different people often use the same words in different ways. EHDEN employs sophisticated technical concepts and methodologies, from data harmonisation using the OMOP Common Data Model to the intricacies of federated data analysis. For someone fresh out of a masters, who’s used to being presented neat, curated datasets, we can say that the size (and chaos) of real world data left something of an impression... What really helped me with this was the project’s provision of continuous education throughout the process. At each EHDEN meeting, there were classes and workshops and through this, I was able to broaden my range of skills and understanding. Plus, the study-a-thons were an invaluable learning opportunity to really expand outside of my field.
Another significant challenge was the interdisciplinary nature of the project. Collaborating with experts from various fields—data scientists, epidemiologists, healthcare professionals, and policy makers—necessitated a holistic understanding of each domain's language and priorities. Effective communication and collaboration were key to making meaningful contributions to the project.
Here are some of the key learnings that have stood out:
The Power of Data Harmonisation:
One of my most profound realisations was the importance of data harmonisation in enabling international health research. The standardised data model facilitates the comparison and analysis of health data from different sources, leading to more robust and generalisable findings. This understanding underscored the significance of meticulous data cleaning and transformation processes. For my own work in prediction modelling, the EHDEN network and the perspective of federated network analyses, enabled me to develop ideas and methods that would have been significantly harder outside of this. One of the key chapters in my thesis focussed on the use of federated networks to improve prediction model development and evaluation.
Problem-Solving Skills:
One of the critical skills I’ve developed is troubleshooting complex problems under pressure. Whether it’s debugging code or resolving data discrepancies, the ability to methodically approach and solve problems has been crucial. This experience has not only enhanced my technical skills but also my confidence in handling unexpected challenges, to see the odd things we sometimes see in our data as an opportunity to dive down an interesting rabbit hole. Specifically, the environments found in the study-a-thons allow not just the rapid development of models and research, but one also gains insights into how others think and problem solve. In a typical asynchronous collaboration, you see the results of these processes, but seeing and participating in the processes themselves is incredibly valuable.
Growth and career development:
Another thing I feel makes EHDEN so exceptional is the way the project trains and develops the people involved. All around me I saw people developing skills and then immediately demonstrating these within their research. This was an incredibly powerful learning process. The project also demonstrated trust in the people it trained (for instance, I now lead Work Package 3 – Personalised Medicines and Federated Networks, having started as a fresh-faced PhD).
Being a PhD student in the EHDEN project has truly been a transformative journey. The challenges have been significant, but the learnings and personal growth have been even greater. This experience has equipped me with a unique set of skills and insights, preparing me for a future in health data research and beyond. The project continues to serve as source of learning, and possibly more importantly - a source of inspiration for how a successful project like is making such an impact in healthcare.
Ross Williams
EHDEN Work Package 3 Lead
Assistant Professor of Health Data Science,
Erasmus Medical Center, Rotterdam, The Netherlands