HDSI Project
Hospital Agent-based Model (HABM)
Hospitals are complex systems composed of highly interdependent pieces. Understanding complex systems is not possible through descriptive or predictive analytics alone. Therefore, to help hospital leaders explore how different decision scenarios effect operations, we utilized simulation modeling. Agent-based modeling simulation methods can be used to visualize how a hospital handles its patient flow and aid in optimizing its processes, or project the impact of future expansion.
Transforming Healthcare
UChicago Medicine’s Digital Twin
What is a Digital Twin?
The Digital Twin is the virtual representation of a physical object or system across its life-cycle. It uses real-time data and other sources to enable learning, reasoning and dynamically recalibrating for improved decision making equipment and forreducing harm to individuals.
Within healthcare a “Digital Twin” would ideally be an exact replica of a complete human body that displays all physiological and pathological outcomes in the present and future, all mapped out in a highly detailed visual.
-Challenge Advisory, www.challenge.org
UChicago Medicine’s Digital Twin helps to understand how parameters such as patient length of stay, adding new beds, and a trauma service effect hospital occupancy.
Insights help UChicago Medicine in decision marking about trauma services.
Evidence from the Field
Simulation Modeling of Patient Flow in an Adult Emergency Department
Resource limitations, steadily increasing patient volumes and acuity, and overcrowded hospitals makes managing an emergency department (ED) an extremely complex problem. While analyzing individual steps in the ED workflow yields valuable insight, it’s often difficult to understand how changing an individual step will effect the overall system. In response a simulation model of the Adult ED at UCMC was created to help ED leadership with clinical operations.