Open AccessProjecting coronary heart disease incidence and cost in Australia: Results from the Incidence module of the Cardiovascular Disease Policy Model
Author(s) -
Mui SuetLam
Publication year - 1999
Publication title -
australian and new zealand journal of public health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.946
H-Index - 76
eISSN - 1753-6405
pISSN - 1326-0200
DOI - 10.1111/j.1467-842x.1999.tb01199.x
Subject(s) - medicine , incidence (geometry) , population , cohort , coronary heart disease , emergency medicine , risk factor , disease , health care , demography , medical emergency , environmental health , sociology , physics , optics , economics , economic growth
Objective: To project the incidence rates of coronary heart disease and the number of hospitalised incident coronary heart disease cases and hospital costs associated with the first hospital admission, for males and females aged 45–69, up to 2014 in Australia. Method: A computer simulation model using a microsimulation technique was developed to simulate individuals' coronary heart disease history over time for a sampled Australian population characterised by major coronary risk factors. Using the simulated incidence rates, population and hospital cost data, the number of hospitalised incident coronary heart disease events and hospital costs associated with the first hospital admission were projected. Results and conclusions: If current cohort‐specific coronary risk factor distributions change only by a location shift and the availability and efficacy of current treatment patterns prevail, the model projects declines of 13% and 24% in incidence rates for males and females aged 45–69 respectively by 2014. However, because the population aged 45–69 is projected to increase over the same period, the number of projected hospitalised coronary heart disease events and the hospital costs associated with the first admission will increase by more than 40%. Implications: A modeling strategy which integrates information on coronary risk factor distributions, epidemiologic, demographic and economic data can provide comprehensive projections that assist future health care planning in the area of coronary heart disease.