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Published online by Cambridge University Press:  20 March 2013

William K. Evans
Juravinski Cancer Centre at Hamilton Health Sciences and McMaster University
Michael C. Wolfson
Population Health Modeling/Populomics, University of Ottawa
William M. Flanagan
Health Analysis and Modeling Divisions, Statistics Canada
Janey Shin
Canadian Partnership Against Cancer
John Goffin
Juravinski Cancer Centre at Hamilton Health Sciences and McMaster University
Anthony B. Miller
Dalla Lana School of Public Health, University of Toronto
Keiko Asakawa
Health Analysis and Modeling Division, Statistics Canada
Craig Earle
Institute for Clinical Evaluative Sciences andUniversity of Toronto
Nicole Mittmann
Centre for Health Outcomes and Pharmacoeconomic Evaluation, Sunnybrook Health Sciences Centre andUniversity of Toronto
Lee Fairclough
Canadian Partnership Against Cancer
Jillian Oderkirk
Health Analysis and Modeling Divisions, Statistics Canada
Philippe Finès
Health Analysis and Modeling Divisions, Statistics Canada
Stephen Gribble
Health Analysis and Modeling Divisions, Statistics Canada
Jeffrey Hoch
Pharmacoeconomics Research Unit, Cancer Care Ontario; The Keenan Research Centre, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Canada; Canadian Centre for Applied Research in Cancer Control (ARCC), Canada; Institute of Health Policy, Management and Evaluation, University of Toronto
Chantal Hicks
Health Analysis and Modeling Divisions, Statistics Canada
D. Walter R. Omariba
Health Analysis and Modeling Divisions, Statistics Canada
Edward Ng
Health Analysis and Modeling Divisions, Statistics Canada


Objectives: The aim of this study was to develop a decision support tool to assess the potential benefits and costs of new healthcare interventions.

Methods: The Canadian Partnership Against Cancer (CPAC) commissioned the development of a Cancer Risk Management Model (CRMM)—a computer microsimulation model that simulates individual lives one at a time, from birth to death, taking account of Canadian demographic and labor force characteristics, risk factor exposures, and health histories. Information from all the simulated lives is combined to produce aggregate measures of health outcomes for the population or for particular subpopulations.

Results: The CRMM can project the population health and economic impacts of cancer control programs in Canada and the impacts of major risk factors, cancer prevention, and screening programs and new cancer treatments on population health and costs to the healthcare system. It estimates both the direct costs of medical care, as well as lost earnings and impacts on tax revenues. The lung and colorectal modules are available through the CPAC Web site ( to registered users where structured scenarios can be explored for their projected impacts. Advanced users will be able to specify new scenarios or change existing modules by varying input parameters or by accessing open source code. Model development is now being extended to cervical and breast cancers.

Copyright © Cambridge University Press 2013

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