VA-CAUSAL is a new causal inference research initiative within the Veterans Health Administration. The goal of VA-CAUSAL is to help transform the VA into a learning health system that expedites the translation of research into practice and supports decision-making by patients, clinicians, and other stakeholders to improve health.
The Methods Core of VA-CAUSAL develops and applies causal inference methods using large-scale data resources at the VA, including electronic health records and the Million Veterans Program multi-omics biobank. Our projects include explicit emulation of target trials of sustained treatment strategies using real-world data, advanced instrumental variable estimation for Mendelian randomization, and estimation of per-protocol effects in randomized trials. The methods, computer code and materials generated during these projects are optimized for use by investigators in the VA research ecosystem and, in collaboration with the Implementation Core of VA-CAUSAL, made available to them.
The VA-CAUSAL Methods Core is a collaboration between the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the Boston VA and the CAUSALab at the Harvard T.H. School of Public Health. It is funded by the Cooperative Studies Program of the U.S. Department of Veterans Affairs as part of the study CSP #2032.