Predicting the Ambulance Offload Delay Problem Using Decision Tree Analysis

When emergency departments (EDs) are congested and cannot accept incoming ambulance patients immediately, a common action is to let paramedics continue to provide patient care until an ED bed becomes available. This delay in transferring a patient from the ambulance to the ED is referred to as ambulance offload delay (AOD). AOD is a growing problem in Canada as the time to transfer an ambulance patient to an ED can be significant. This can negatively affect the ability of the ambulance service to respond to future calls and reduces the efficiency of the system. Using integrated historical data from a partnering hospital and partnering Emergency Medical Services (EMS) provider, a decision tree model will be developed to predict AOD of the system in a proposed period. The development of this prediction model can help ambulance service providers to be proactive with the potential AOD problem by activating interventions to prevent it from occurring.

Faculty Supervisor:

Peter VanBerkel

Student:

Partner:

University of Florida

Discipline:

Engineering

Sector:

Health and Related Sciences & Technology

University:

Dalhousie University

Program: