In creating a graph of events in a hospital we ran into problems trying to graph the locations of patients over both time and space. This talk will give practical tips and code on how we were able to model both space and time in our graph.
We created a graph database of patient data in the hospital. We wanted to be able to model a patient’s hospitalization including diagnoses, consults, infections, procedures, tests, etc. It was important to us to be able to look at events across both time and space. We wanted to be able to ask questions like “who got an infection during their stay and who was sharing a room with them at the time they contracted that infection?” We had difficulty modeling this relationship of both space and time. This talk will discuss the model we used to answer this and other questions and to model the relationships of events through both space and time.
Analytics Project Leader, New York Presbyterian Hospital
Michael Zelenetz is an Analytics Project Leader at New York Presbyterian. He used to save lives as a paramedic, now he uses data to improve care and patient experience.
Thursday September 20, 2018 11:45am - 12:00pm EDT
6. Wilder