UBC Theses and Dissertations
Direct cost of osteoarthritis in Canada : an application of microsimulation modeling with uncertainty analysis Sharif, Behnam
Introduction: While OA is a debilitating disease with an immense economic burden on the Canadian society, there is a lack of understanding about OA’s direct costs and its future trend in Canada. Objectives: The overall goal of this thesis is to illustrate the application of population-based disease microsimulation (PDMS) modeling in estimating the economic burden of a disease by performing the direct cost analyses for osteoarthritis (OA) using Population Health Microsimulation Model for OA (POHEM-OA). Specific objectives were: 1) To estimate the average direct costs of OA from 2003 to 2010 in Canada; 2) To estimate the future direct cost of OA from 2010 to 2031 in Canada; 3) to estimate the uncertainty around the prevalence and total cost of OA in future years. Methods: I used administrative health data from the province of British Columbia (BC), Canada, a survey of a random sample of BC residents diagnosed with OA (Ministry of Health of BC data), Canadian Institute of Health Information (CIHI) cost data and literature estimates to perform a bottom-up cost of illness (COI) study for OA. I then implemented the results of the COI study into POHEM-OA and constructed cost profiles for each individual. Finally, I developed a framework and adapted an ANOVA-based approach for performing uncertainty analysis (UA) for OA outcomes. Results: I showed that the average cost increased from $735 to $811 between 2003 and 2010 (in 2010 $CAD). From 2010 to 2031, while the prevalence of OA increases from 13.8% to 18.6%, the total direct cost of OA is projected to increase from $2.9 billion (95% uncertainty interval (UI): $2.4-$3.1 billion), to $7.6 billion ($6.2-$9.1 billion), an almost 2.6-fold increase (in 2010 $CAD). From the highest to the lowest, the cost components that will constitute the total direct cost of OA in 2031 are hospitalization cost, outpatient services, drugs, and out-of-pocket cost categories. Conclusions: By further developing a PDMS model of OA, I were able to project trends in the cost of OA and identify the key cost drivers, while predicting significant shifts in distribution of cost in the future.
Item Citations and Data
Attribution-NonCommercial-NoDerivs 2.5 Canada