Western University Computer ScienceWestern Science

MSc Thesis Defense


Annette Megerdichian Azad

Mining of Primary Healthcare Patient Data with Selective Multimorbid Diseases


Thesis Examiners:

Thursday, May 4, 2017
9:30 a.m.
Middlesex College, Room 320
Dr. Mike Bauer
Dr. Dan Lizotte
Dr. Kamran Sedig

Dr. Jaquelyn Burkell (FIMS)
Dr. Sylvia Osborn



Despite a large volume of research on the prognosis, diagnosis and overall burden of multimorbidity, very little is known about socio-demographic characteristics of multimorbid patients. This thesis aims to analyze the socio-demographic characteristics of patients with multiple chronic conditions (multimorbidity), focusing on patient groups sharing the same combination of diseases. Several methods were explored to analyze the co-occurrence of multiple chronic diseases as well as the correlations between socio-demographics and chronic conditions. These methods include disease pair distributions over gender, age groups and income level quintiles, Multimorbidity Coefficients for measuring the concurrence of disease pairs and triples, and k-modes clustering to examine the demographics of patients with the same chronic condition. The experiments suggest that patient income quintile does not affect multimorbidity rates, although gender and age group may play an important role in prevalence of multimorbidity and diagnosis of certain disease combinations.