Data Analysis and Development of Cost Prediction Method for Renal Failure Care Delivery

Care of patients with renal disease is important and resource intense. Since we have an aging population with an increase in diabetes prevalence; the number of patients with renal disease is increasing and there is a need to develop strategies for more cost efficient care. The solution to this issue is home dialysis which is an alternative to the conventional hospital-treatment. Home dialysis is able to reduce the cost of the care delivery and also enhance the quality of health care for the patient. This process is monitored and facilitated by eQOL using a novel mobile technology solution. The goal of this project is to collect the data, gathered from home dialysis patients either electronically or by Health Care Team, and analyze it to quantify and predict the cost care delivery across different patient groups and time periods. This prediction will be able to forecast the total cost of care in a time period for a given patient with a set of input data. This information is valuable to health care administrators to accurately quantify the cost of care delivery and plan the budget accordingly.

Faculty Supervisor:

Chao Zhang

Student:

Partner:

eQOL Inc

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology; Information and Communications Technology; Public Service, Policy, and Governance

University:

Western University

Program: