Electronic Thesis and Dissertation Repository

Degree

Doctor of Philosophy

Program

Epidemiology and Biostatistics

Supervisor

Dr. Amardeep Thind

2nd Supervisor

Dr. Amanda Terry

Joint Supervisor

Abstract

Introduction: The coexistence of multiple chronic diseases within an individual, also known as multimorbidity, is an ongoing challenge for patients, caregivers and primary health care (PHC) providers. An enhanced understanding of the burden of multimorbidity in Canada is needed.

Objectives: This research had two main objectives. Objective One aimed to understand the prevalence of multimorbidity among adult PHC patients, as well as the patterns of unordered and ordered clusters of multiple chronic diseases. Objective Two aimed to determine the natural progression of multimorbidity over time, as well as the patient-, provider- and practice-level predictors of progressing into more complex clinical profiles.

Methods: Data were derived from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) electronic medical record (EMR) database. For Objective One, descriptive and computational analyses were conducted and for Objective Two, multilevel survival analyses were conducted to account for clustering. Patients with at least one encounter recorded in their EMR and who were at least 18 years of age at their first encounter were included in the analyses. Chronic disease diagnoses were identified using the International Classification of Diseases, 9th Revision (ICD-9) and a list of 20 chronic disease categories identified patients with multimorbidity.

Results: Overall, 53.3% and 33.1% of adult PHC patients were living with at least two and at least three chronic diseases, respectively. Patients with at least two chronic diseases had a mean age of 59.0 years (SD: 17.0), while the majority were female (57.8%) and living in an urban setting (52.2%). Among female patients with multimorbidity, 6,095 unique combinations and 14,911 unique permutations were found. Among male patients with multimorbidity, 4,316 unique combinations and 9,736 unique permutations were detected. The multilevel survival analysis indicated that several patient-level (patient age, patient sex and total number of chronic diseases), provider-level (provider age) and practice-level (EMR type and practice location) variables predicted time until subsequent chronic disease diagnoses.

Conclusion: This research explored the prevalence, patterns and natural progression of multimorbidity over time among a large cohort of adult PHC patients. When carefully assessed, these findings will help to create a more nuanced understanding of the burden of multimorbidity.


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