Hossein Abouee Mehrizi

Canada Research Chair in Health Care Analytics

Tier 2 - 2014-02-01
Renewed: 2019-02-01
University of Waterloo
Canadian Institutes of Health Research

519-888-4567, ext. 35240

Research involves

Developing a dynamic, multi-class, multi-priority patient scheduling method in health care.

Research relevance

This research will improve the way we schedule patients and improve the health care system’s ability to meet wait-time targets.

A Better Way to Schedule Patients and Respect Wait Times

Canadians are generally proud of their health care system’s universal access. But universal access coupled with ever-increasing demand can make it challenging for the system to keep up with patients’ needs. The result: wait times for health services.

Waiting for health services can cause patients great pain and anxiety, and lead to deterioration in their quality of life. Waiting for care in an emergency department, in particular, can put patients’ lives at risk.

In response, Canada has adopted a triage system that prioritizes patients based on their acuity level. The Canadian Triage & Acuity Scale (CTAS) assigns patients a score of 1 to 5 depending on their condition. To ensure patients with less urgent scores don’t wait an unreasonably long time, hospitals set targets for wait times by acuity level.

Despite these efforts, there is still room to improve health care wait times in Canada—and that is what Dr. Hossein Abouee Mehrizi is working on. As Canada Research Chair in Healthcare Analytics, Abouee Mehrizi is developing and analyzing a multi-class, multi-priority dynamic scheduling model for patients with wait time targets. This new model will consider the relationship between wait times, rates of cancellations and no-shows, scheduling windows, patient prioritization policies, and length of stay. It will also empirically validate the developed model using historical data.

Ultimately, Abouee Mehrizi and his research team aim to come up with a patient scheduling method that will increase the volume of patients treated and decrease patients’ wait times.