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In many developed countries, the burden of disease has shifted from acute to long-term or chronic diseases – producing new and broader challenges for patients, healthcare providers, and healthcare systems. Multimorbidity, the coexistence of two or more chronic diseases within an individual, is recognized as a significant public health and research priority. This protocol aims to examine the prevalence, characteristics, and changing burden of multimorbidity among adult primary healthcare (PHC) patients using electronic medical record (EMR) data. The objectives are two-fold: (1) to measure the point prevalence and clusters of multimorbidity among adult PHC patients; and (2) to examine the natural history and changing burden of multimorbidity over time among adult PHC patients. Data will be derived from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN). The CPCSSN database contains longitudinal, point-of-care data from EMRs across Canada. To identify adult patients with multimorbidity, a list of 20 chronic disease categories (and corresponding ICD-9 codes) will be used. A computational cluster analysis will be conducted using a customized computer program written in JAVA. A Cox proportional hazards analysis will be used to model time-to-event data, while simultaneously adjusting for provider- and patient-level predictors. All analyses will be conducted using STATA SE 13.1. This research is the first of its kind using a pan-Canadian EMR database, which will provide an opportunity to contribute to the international evidence base. Future work should systematically compare international research using similar robust methodologies to determine international and geographical variations in the epidemiology of multimorbidity.

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