A Markov simulation model for analyzing and forecasting the number of coronary artery revascularization procedures in Western Australia

Haider R. Mannan, Matthew Knuiman, Michael Hobbs

    Research output: Contribution to journalArticlepeer-review

    2 Citations (Scopus)

    Abstract

    PURPOSE: A Markov chain Monte Carlo simulation model was developed to analyse and forecast the numbers of coronary artery bypass graftings, percutaneous coronary interventions (PCIs), incident coronary heart disease (CHD) events, and CHD deaths for different age and sex groups in the population of Western Australia (population approximately 1.7 million). METHODS: The Western Australian health information system contains linked records of all hospital admissions and deaths for individuals from 1980 to the present. This system allows the separation of the population into groups according to CHD/coronary artery revascularization procedure history and also allows the estimation of event probabilities directly from population-level data. RESULTS AND CONCLUSIONS: The results for the 1990 Western Australian population over the period 1990 to 1994 and the 1995 population over the period 1995 to 1999 indicated that the Markov model fits well and produces good forecasts under “stable” conditions. The model can also be useful in ascertaining the impact of system changes, such as the widespread introduction of stents in PCI operations in 1995.
    Original languageEnglish
    Pages (from-to)964-975
    Number of pages12
    JournalAnnals of Epidemiology
    Volume17
    Issue number12
    DOIs
    Publication statusPublished - 2007

    Keywords

    • Markov processes
    • Monte Carlo method
    • coronary heart disease
    • myocardial revascularization

    Fingerprint

    Dive into the research topics of 'A Markov simulation model for analyzing and forecasting the number of coronary artery revascularization procedures in Western Australia'. Together they form a unique fingerprint.

    Cite this