TY - JOUR
T1 - Sex, obesity, diabetes, and exposure to particulate matter among patients with severe asthma
T2 - Scientific insights from a comparative analysis of open clinical data sources during a five-day hackathon
AU - The Biomedical Data Translator Consortium
AU - Fecho, Karamarie
AU - Ahalt, Stanley C.
AU - Arunachalam, Saravanan
AU - Champion, James
AU - Chute, Christopher G.
AU - Davis, Sarah
AU - Gersing, Kenneth
AU - Glusman, Gustavo
AU - Hadlock, Jennifer
AU - Lee, Jewel
AU - Pfaff, Emily
AU - Robinson, Max
AU - Sid, Eric
AU - Ta, Casey
AU - Xu, Hao
AU - Zhu, Richard
AU - Zhu, Qian
AU - Peden, David B.
N1 - Publisher Copyright:
© 2019 Elsevier Inc.
PY - 2019/12
Y1 - 2019/12
N2 - This special communication describes activities, products, and lessons learned from a recent hackathon that was funded by the National Center for Advancing Translational Sciences via the Biomedical Data Translator program (‘Translator’). Specifically, Translator team members self-organized and worked together to conceptualize and execute, over a five-day period, a multi-institutional clinical research study that aimed to examine, using open clinical data sources, relationships between sex, obesity, diabetes, and exposure to airborne fine particulate matter among patients with severe asthma. The goal was to develop a proof of concept that this new model of collaboration and data sharing could effectively produce meaningful scientific results and generate new scientific hypotheses. Three Translator Clinical Knowledge Sources, each of which provides open access (via Application Programming Interfaces) to data derived from the electronic health record systems of major academic institutions, served as the source of study data. Jupyter Python notebooks, shared in GitHub repositories, were used to call the knowledge sources and analyze and integrate the results. The results replicated established or suspected relationships between sex, obesity, diabetes, exposure to airborne fine particulate matter, and severe asthma. In addition, the results demonstrated specific differences across the three Translator Clinical Knowledge Sources, suggesting cohort- and/or environment-specific factors related to the services themselves or the catchment area from which each service derives patient data. Collectively, this special communication demonstrates the power and utility of intense, team-oriented hackathons and offers general technical, organizational, and scientific lessons learned.
AB - This special communication describes activities, products, and lessons learned from a recent hackathon that was funded by the National Center for Advancing Translational Sciences via the Biomedical Data Translator program (‘Translator’). Specifically, Translator team members self-organized and worked together to conceptualize and execute, over a five-day period, a multi-institutional clinical research study that aimed to examine, using open clinical data sources, relationships between sex, obesity, diabetes, and exposure to airborne fine particulate matter among patients with severe asthma. The goal was to develop a proof of concept that this new model of collaboration and data sharing could effectively produce meaningful scientific results and generate new scientific hypotheses. Three Translator Clinical Knowledge Sources, each of which provides open access (via Application Programming Interfaces) to data derived from the electronic health record systems of major academic institutions, served as the source of study data. Jupyter Python notebooks, shared in GitHub repositories, were used to call the knowledge sources and analyze and integrate the results. The results replicated established or suspected relationships between sex, obesity, diabetes, exposure to airborne fine particulate matter, and severe asthma. In addition, the results demonstrated specific differences across the three Translator Clinical Knowledge Sources, suggesting cohort- and/or environment-specific factors related to the services themselves or the catchment area from which each service derives patient data. Collectively, this special communication demonstrates the power and utility of intense, team-oriented hackathons and offers general technical, organizational, and scientific lessons learned.
KW - Application programming interface
KW - Clinical data
KW - Hackathon
KW - Multi-institutional collaboration
KW - Open data
KW - Team science
UR - http://www.scopus.com/inward/record.url?scp=85074882444&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85074882444&partnerID=8YFLogxK
U2 - 10.1016/j.jbi.2019.103325
DO - 10.1016/j.jbi.2019.103325
M3 - Comment/debate
C2 - 31676459
AN - SCOPUS:85074882444
SN - 1532-0464
VL - 100
JO - Journal of Biomedical Informatics
JF - Journal of Biomedical Informatics
M1 - 103325
ER -