Jing Li is an Associate Director of Data Science at IQVIA, where she is leading a global team of data scientists on real world studies, focusing on treatment patterns, and drug safety studies. She has several years of industry experience in predictive modeling, machine learning, and data management, and she decided to focus her work on healthcare research in 2019.
Jing has grown into a leader in the OHDSI Asia-Pacific (APAC) Community. She leads the bi-weekly APAC community calls and is part of the steering group for both the APAC workgroup and APAC symposium planning committee. She was also a co-author on the first ever network study published by the APAC workgroup, Analysis of Dual Combination Therapies Used in Treatment of Hypertension in a Multinational Cohort.
In our most recent edition of the Collaborator Spotlight, Jing discusses her career and how she moved into healthcare, her excitement about the growing APAC community, and plenty more.
What is your background, and how did you develop an interest in data science?
After majoring in ocean engineering (ship building stuff 😊) for 4 years in undergrad, I found out that I am more interested in the fundamental math classes. I am very thankful that the Statistics Department of the University of Minnesota admitted me and then it was love at first sight after that, and I really enjoyed using the power of data to answer questions and make decisions.
What is your role with IQVIA, and how did you first connect with OHDSI?
I am Associate Director of Data Science in IQVIA OMOP team, and responsible for analytics projects within the team. I joined IQVIA in 2019, and was introduced to OHDSI community right away by Mui Van Zandt. I have the pleasure of working closely with OHDSI China community, and the broader OHDSI APAC community.
You have taken a leadership role within our Asia-Pacific community. Can you share some of the recent APAC developments you are most proud of?
Tough question, so many to choose from! I would say I am most proud of the first OHDSI APAC LEGEND HTN paper we collaborated together with the whole APAC community, which was published in JAMA Network Open this March. It is great to see the fruit of labor from the community, and we wish there are more coming up. Also, I am very proud that we have been doing bi-weekly APAC community calls since Jan 2021, which has been a great time for APAC community to get together, share, and learn.
The APAC leads have taken on four network studies this year, and you were a co-author on the first full APAC study published in JAMA Network Open earlier this year. How important is connecting researchers together in APAC, and how exciting has it been to see this progress?
As the six APAC chapters are all new to OHDSI community, it is very beneficial for the researchers to get together and share experience. We started the APAC LEGEND HTN back in early 2020, and thinking back, it was such a fulfilling journey of getting the protocol ready by gathering feedback from different chapters, doing data quality checks for the first time OHDSI data partners, and finally interpreting the results. A very rewarding collaboration indeed.
You have years of experience in predictive modeling. How do OHDSI tools and best practices enhance our ability to work on prediction research?
For me, as much as I love to write my own codes, there are always the concerns and additional review work needed in order to make sure the codes are correct with no bugs. With all the OHDSI tools, I really appreciate the perspective that they have been validated by the community, which essentially speed up the analysis time needed.
You are seeing the growth of our community worldwide, but what inspires you most about OHDSI, and why do you think it is spreading so rapidly?
There is a saying in Chinese – 酒香不怕巷子深, which could be translated into ‘Good wine needs no bush’. I really think the reason is because OHDSI has great methodologies, tools, and community support, which are making more and more people adopt OMOP and join the community.
What are some of your hobbies, and what is one interesting thing that most community members might not know about you?
As I was not in healthcare industry before joining IQVIA, I am relatively new to everything medical, so I took my learning very ‘seriously’ by watching House MD and Good Doctor, and read books like This is going to hurt 😊.