The Health Care Optimization and Analytics Lab, H-COAL (https://www.h-coal.com), at Dalhousie University’s Department of Industrial Engineering is seeking a Postdoctoral Fellow for a 2-year term. The position is funding by Mitacs Accelerate with matching funds from Synaptive Medical.
Synaptive Medical has developed the 0.5 T Evry MRI that is a smaller MRI device that is ideal for brain imaging, and it has the potential to improve outcomes for stroke patients and reduce health system costs. A Synaptive 0.5 T Evry MRI has been installed for research purposes at the Halifax’s Queen Elizabeth II Health Centre (QEII).
The objective of this research will be to evaluate the potential improvement in patient outcomes and cost avoidance to the health system and the patient through the use of the Synaptive 0.5 T Evry MRI for acute stroke patients. The methodology to meet the objective will be carried out in three phases. In the first phase, various patient profiles will be defined for patients that will benefit from this device; this work will be carried out in close collaboration with clinical experts. In the second phase, the profiles identified in phase 1 will be reviewed and their baseline outcomes and costs will be determined; secondly, models of patient outcomes, health system costs and patient/family costs will be developed. The final phase will quantify the potential improvement in patient outcomes and reduction in health system and patient/family costs through the use of the device.
The Postdoctoral Fellow (PDF) will carry out all aspects of this project. The PDF will be responsible for obtaining the necessary ethics and data access approvals. They will work in collaboration with NS Health, representatives from Synaptive Medical, and clinicians at QEII.
The ideal candidate must hold a PhD in Epidemiology, Health Administration, Industrial Engineering or a related field. The ideal candidate should have the following:
- Knowledge of acute stroke
- Experience working in a hospital setting
- Knowledge of health care systems
- Developing models (such as statistical models) of health outcomes
- Knowledge of health care costing and/or health economics