A method, system, and computer program product for parallelization of updating synthetic events with genetic surprisal data comprising dividing the synthetic event into cohort parts and assigning the cohort parts to one of a plurality of computer processing elements. Within each processing element: searching data records of patients for genetic surprisal data; generating a cluster comprising a centroid by populating the cluster based on all of the matches of the data records; calculating a new centroid for each cluster; calculating a Euclidean distance in multiple dimensions for each match of data records to the new centroid for each cluster; reassigning each match of data to the new centroid of each cluster based on the shortest calculated Euclidean distance to the new centroid for each cluster; and determining at least one cohort part from the clusters and recombining the cohort parts into updated synthetic events based on the metadata.