Osteoarthritis and Cartilage
Volume 18, Issue 3 , Pages 303-311, March 2010

Development of a population-based microsimulation model of osteoarthritis in Canada

  • J.A. Kopec

      Affiliations

    • University of British Columbia, Vancouver, BC, Canada
    • Arthritis Research Centre of Canada, Vancouver, BC, Canada
    • Corresponding Author InformationAddress correspondence and reprint requests to: J. A. Kopec, School of Population and Public Health, University of British Columbia, Research Scientist, Arthritis Research Centre of Canada, 895 West 10th Avenue, Vancouver, BC V5Z 1L7, Canada. Tel: 1-604-871-4588; Fax: 1-604-879-3791.
  • ,
  • E.C. Sayre

      Affiliations

    • University of British Columbia, Vancouver, BC, Canada
    • Arthritis Research Centre of Canada, Vancouver, BC, Canada
  • ,
  • W.M. Flanagan

      Affiliations

    • Statistics Canada, Ottawa, ON, Canada
  • ,
  • P. Fines

      Affiliations

    • Statistics Canada, Ottawa, ON, Canada
  • ,
  • J. Cibere

      Affiliations

    • University of British Columbia, Vancouver, BC, Canada
    • Arthritis Research Centre of Canada, Vancouver, BC, Canada
  • ,
  • Md.M. Rahman

      Affiliations

    • Arthritis Research Centre of Canada, Vancouver, BC, Canada
  • ,
  • N.J. Bansback

      Affiliations

    • Centre for Health Economics and Outcome Sciences, St. Paul's Hospital, Vancouver, BC, Canada
  • ,
  • A.H. Anis

      Affiliations

    • University of British Columbia, Vancouver, BC, Canada
    • Arthritis Research Centre of Canada, Vancouver, BC, Canada
    • Centre for Health Economics and Outcome Sciences, St. Paul's Hospital, Vancouver, BC, Canada
  • ,
  • J.M. Jordan

      Affiliations

    • University of North Carolina, Chapel Hill, NC, USA
  • ,
  • B. Sobolev

      Affiliations

    • University of British Columbia, Vancouver, BC, Canada
  • ,
  • J. Aghajanian

      Affiliations

    • Arthritis Research Centre of Canada, Vancouver, BC, Canada
  • ,
  • W. Kang

      Affiliations

    • Arthritis Research Centre of Canada, Vancouver, BC, Canada
  • ,
  • N.V. Greidanus

      Affiliations

    • University of British Columbia, Vancouver, BC, Canada
    • Arthritis Research Centre of Canada, Vancouver, BC, Canada
  • ,
  • D.S. Garbuz

      Affiliations

    • University of British Columbia, Vancouver, BC, Canada
    • Arthritis Research Centre of Canada, Vancouver, BC, Canada
  • ,
  • G.A. Hawker

      Affiliations

    • University of Toronto, Toronto, ON, Canada
  • ,
  • E.M. Badley

      Affiliations

    • University of Toronto, Toronto, ON, Canada

Received 4 April 2009; accepted 15 October 2009. published online 20 November 2009.

Summary 

Objectives

The purpose of the study was to develop a population-based simulation model of osteoarthritis (OA) in Canada that can be used to quantify the future health and economic burden of OA under a range of scenarios for changes in the OA risk factors and treatments. In this article we describe the overall structure of the model, sources of data, derivation of key input parameters for the epidemiological component of the model, and preliminary validation studies.

Design

We used the Population Health Model (POHEM) platform to develop a stochastic continuous-time microsimulation model of physician-diagnosed OA. Incidence rates were calibrated to agree with administrative data for the province of British Columbia, Canada. The effect of obesity on OA incidence and the impact of OA on health-related quality of life (HRQL) were modeled using Canadian national surveys.

Results

Incidence rates of OA in the model increase approximately linearly with age in both sexes between the ages of 50 and 80 and plateau in the very old. In those aged 50+, the rates are substantially higher in women. At baseline, the prevalence of OA is 11.5%, 13.6% in women and 9.3% in men. The OA hazard ratios for obesity are 2.0 in women and 1.7 in men. The effect of OA diagnosis on HRQL, as measured by the Health Utilities Index Mark 3 (HUI3), is to reduce it by 0.10 in women and 0.14 in men.

Conclusions

We describe the development of the first population-based microsimulation model of OA. Strengths of this model include the use of large population databases to derive the key parameters and the application of modern microsimulation technology. Limitations of the model reflect the limitations of administrative and survey data and gaps in the epidemiological and HRQL literature.

Key words: Osteoarthritis, Epidemiology, Microsimulation, Modeling, Population, Risk factors, Quality of life, Policy evaluation

 

PII: S1063-4584(09)00282-9

doi:10.1016/j.joca.2009.10.010

Osteoarthritis and Cartilage
Volume 18, Issue 3 , Pages 303-311, March 2010