There is a lot of energy and good will in the community. It is open, inclusive, and extremely diverse. I get my energy from the community. The enthusiasm and drive to do the right thing and to improve human lives and the possibility to work with such diverse group of individuals and learn from them excites me and pushes me to do more. I am extremely proud to be a part of this effort.

OHDSI is a multi-disciplinary community pushing the boundaries of computational observational research so there is always something new to learn. The values of being transparent in our methods and in our software resonate with me in trying to make a lasting impact. I get energized from going to OHDSI meetings because I always meet new people, learn new things, and am part of making a difference in improving healthcare.

What inspires me the most to stay active and a leader is the ability to collaborate to improve our overall health decisions and better care. It’s something I truly believe in as a great cause for ourselves and our future generations. There are so many out there who think just like me and it really shows by the amount of openness and collaboration that is out there in the OHDSI community.

Being part of OHDSI has changed my ideas of how research should be designed, undertaken and reported. I feel that these notions are vital for science to move forward. Being part of this community has definitely changed the way I feel about open science, and that transparency and collaboration are key to the future of epidemiological research during the time of ‘fake news.'

While my time in the OHDSI community is relatively brief, the environment struck a chord with me immediately. What stands out is how the community welcomes expertise from myriad backgrounds. Whether you’re a seasoned researcher, a data scientist, a clinician, or even someone just starting in healthcare analytics, OHDSI is a platform where different levels of familiarity converge to nurture actionable knowledge.

All the useful open-source tools available within the OHDSI community allowed me to build further on existing work and solve new challenges right from the beginning. I am not sure if I fully valued the worth of starting research in an environment with so much data during the beginning of my PhD. It has certainly provided me with very valuable insights in real-world data collection processes that are very helpful to also understand limitations in existing modeling methods.

As an internist, I’ve become a better consumer of observational studies, and predictive model studies in particular. That was very helpful in the COVID era. I was better able to appraise the observational studies that were being published, while OHDSI’s own work produced effect estimates that I was able to confidently bring to the bedside. As an example, I was able to cite the work done by this group when justifying restraint regarding hydroxychloroquine in COVID-19 related respiratory disease to patients and their families.

There is something unique about the OHDSI organization and how they support the community, which motivates the community to work as a whole. We know that with greater diversity and inclusiveness, there is greater creativity and innovation.

OHDSI has six values: Innovation, Reproducibility, Community, Collaboration, Openness, and Beneficence. OHDSI pursues highly reliable evidence through innovative ways and an open-science spirit. When I started my journey in 2016, many gurus in OHDSI welcomed and helped me a lot. OHDSI works hard to produce medical evidence for the better care for humanity. It is truly impressive that OHDSI is trying to hold its values.

I often sit in those teleconferences (often late at night or in the wee hours of the morning here in Australia) and marvel at the discoveries and new insights that are shared so openly. The light bulb moments that lead to fabulous discoveries! The work that has been generated in LEGEND and EUMAEUS is important clinically, it can help to update clinical guidelines and provides robust evidence for medicine regulators – but for me these landmark studies have also provided critical insights into which methodologies are appropriate under which conditions – especially the value of empirical calibration!