Real-time Analytics and Decision Support for Patient Flow Management 2

Large community hospitals and teaching hospitals in Ontario operate at congestion levels most of the time. This translates into long wait times for the patients, cancelled procedures, undue stress for the clinical staff, and inefficiency in hospital operations. In order to address the bottlenecks in patient flows, decisions are made by the clinical staff based on incomplete data which may be several hours to several days old, manually, in an ad hoc manner. Furthermore, these decisions may be optimal for the Unit (the Emergency Department, or the Cardiology Department, for instance), but sub-optimal for the hospital as a whole. Our proposed research project is to investigate an information system to facilitate and guide the decision-making on patient flow management when needed, in order to address the root causes of the bottlenecks, and hence decrease the patient wait times, without increasing the burden on the Clinicians.

Faculty Supervisor:

Liam Peyton

Student:

Partner:

William Osler Health System;University of Ottawa

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology

University:

University of Ottawa

Program: